HF has been a close part of my ML/AI career, coinciding exactly when I moved into this space 10 years ago. There are lot of nuances here (if the deal goes through). Some people say it's a loss for EU sovereign AI but HF is technically an American corporation. On the positive note, the founders (Julien, Thomas and Clem - all French) stem to make significant amount of money, which they are likely to pour into a new frontier AI lab in Europe. So potentially it's a big win. For Nvidia this is a great strategic play as it potentially gains control of the "AI app store" and can influence the direction of Transformers, Diffusers, PEFT and various other HF libs inits favour. At the same time Nvidia has been (somewhat paradoxically) a dominant force in actual "open source" AI and has contributed significantly via Nemotron and various optimisers close to the metal. This would likely accelerate further. Nvidia has everything to gain from having a massive open model ecosystem, instead of a consolidated market consisting of 2-3 players. Will that have impact on MLX and other contributions? We'll see!
And I would say it's actually a more secure future demand channel than the hyperscalers. Openai and co can build their own chips, so they won't buy from NVidia. But they probably won't sell them to somebody else, so everyone who wants to run their own install (and can, not the least because of HF), will buy Nvidia.
It was Nvidia’s competitors’ job to ensure this never happened but hardware companies rarely value the software stack as much as they should have. AMD screwed up several times to build a similar tool and Intel did not manage to create a proper programming model for their vector instruction sets despite having some promising internal efforts. Cuda allowed AlexNet to usher the deep learning era, written by university researchers. The flash attention implementation allowed quadratic attention to have reasonable memory requirements again written by a university professor and used by everyone. If I were to complain about Nvidia, I would complain about them abandoning the personal computing track for datacenter profits, definitely not about pushing Cuda.
Translating CUDA kernels to ROCm (or any other ecosystem, tbh) is going to become trivially easy with AI. Not saying that code is the only glue that Nvidia has when it comes to their ecosystem, but it’s certainly a large part of it.
> which they are likely to pour into a new frontier AI lab in Europe
HF was.. a hub to download models and some of the worst source code in the space that contributed to huge amounts bugs that did a lot of downstream damage. Go ahead and read their blog by their CTO on how they don’t believe in DRY and then implemented DRY in the worst way imaginable with unnecessary code generation.
Their BLOOM model was a joke and dead on arrival.
But yea these guys are definitely going to be the frontier of EU AI.
They’ve provided insane value to the ai community. Imo is there really any obvious way to standardize model/preprocessing/inference/training/rl recipes across the space of frankenstein model family/architecture/modality combinations? It’s not even clear to me that the current frontier would be where it is today without HF doing what they did how they did it. Where else were people widely sharing datasets w that ease of reuse/redistribution, or sharing their retuned models etc? Would there even be as much interest/tinkerers today?
Their strength was the ability to keep at the very fast moving AI frontier.
When a new model is released they have been able to have a working implementation days later, not months when the model was redundant.
And often it's much more usable than the one-off, unmaintained, research code written in a very fragile environment.
BLOOM was a decent fully open and very large model for its time, and a huge coordination effort. It was around the same time as another "joke", OPT, but that gave Meta the knowledge that let them build Llama.
Huggingface didn't have the money to compete in that race, but I'd bet it helped them stay at the frontier of AI software.
Google could have owned this space; they had TensorFlow hub, but it was too hard to use and too locked down. Huggingface made it easy to run and train transformers, and got the timing just right.
I'm glad someone is trying to build truly open models (along with the great work at Allen AI), because the likes of Meta and Alibaba are only going to release weights as long as it suits their business.
It has to be a bell curve doesn't it.. I am too much of a perfectionist...
Then again, my llms constantly claim that I am doing things that are beyond the SOTA. Even my own mom lost hope.. Still haven't shipped a single thing... haha.
(half joke aside, it is finally coming in a couple days.. which I have been saying for quite some time to the extent that my peeps don't even trust me anymore.. 3 things are coming and it is genuinely research grade apparently, for the amount of research I am aware that is released publicly.
I really don't know how people ship things, the tooling I see is terrible, or maybe I have NIH syndrome...)
"The company was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf in New York City, originally as a company that developed a chatbot app targeted at teenagers. ..." Wikipedia
Besides that: which EU and sovereignty doesn't really rhyme, given data protection, energy costs, AI restrictions and no vital start up scene at all.
Mistral is heavily state funded via Banks that are predominantly owned by the French state, so I don't get it.
Also name one global success that doesn't came from US? China? Well, second place maybe, but second in any sense.
Nevertheless, kudos to huggingface. Not only to the founders, but to the ecosystem and I guess it got harder by the day to finance all the hosting and only hope for the future, that Nvidia will help HF to thrive, at least not put burdens on them.
GitHub is still alive, and hope that HF will benefit from more AI power.
Nvidia doesn't have any disadvantages in my playbook, because hardware wise, there is no one to beat them in any regard and Apple will always stay nichy.
So well played - hopefully.
It could be worse or even a shut down otherwise, who knows. So for me it sounds cool and I am glad that EU isn't involved in any regard.
As the AI Act demands full disclosure under really easy to match requirements into your inner workings, this is quite the opposite of freely sharing information.
The list goes on for products and services they cloned from western innovation. China didn't get there first in any of the categories you listed. Of course, people would rather spend less than more, disregarding the quality and longevity of the product.
Paying pennies on the dollar for a BYD vehicle sounds great when all you consider is the initial sticker price. The real cost is what happens after you buy the disposable car and own it for a decade.
So yea. Second place is the reality and it is also true for AI models, and the hardware needed to run them.
Also, congratulations on landing a rocket 11 years after the US.
From where I’m sitting in Europe, Tesla feels like the disposable car. Gatekeeping repairs and parts and more quality defects needing post shipment corrections than other brands.
To take a concept and refine it to reach mass production is success. It is what made the US what you believe it is today and it is what is creating a healthy supply chain in China. Just look at the challenges of Destin of Smarter Every Day[1] when producing a grill scrubber using only US suppliers and materials.
A “Made in the USA” label is no guarantee of superior design or manufacturing quality to me but if Japan is mentioned I have a greater confidence in the quality of the product.
Sorry but you're talking absolute nonsense, Europe has no global successes?
How about...
SAP (Germany) - Most of the Fortune 500 run on their software.
Spotify (Sweden)
Novo Nordisk (Denmark) - most of America is taking their drugs.
Airbus (France) - Has out competed and out delivered Boeing for years.
Ericsson and Nokia (Finland and Sweden) - Most of American telecom systems use tech from them, essentially the western alternative to Huawei in telecom networking.
Adyen (Netherlands) - One of the worlds largest payment processors, processes most of American big tech payments.
ASML (Netherlands) - Responsible for building effectively every modern chip in the world outside of China.
Maersk (Shipping and logistics)
Siemens (Industrial Tech)
Infineon (Semis)
And there are so many more I'm missing btw. It's funny how incredibly biased you are, but the reality is that Europe and the USA are totally dependent on each other, tech wise.
If every European company which the US is dependent on immediately stopped trading with the US, the US would collapse as a country. And yes, the opposite is true also. But it was you who argued that Europe effectively has no successful companies, what rubbish.
SAP isn’t a company to be crazy proud of, but it doesn’t make it not a success nor does it mean “EU is fucked”.
May I remind you that in the US, Facebook is in that same list of top successes? Have you ever heard the phrase “the top minds of this generation of Americans are all working on ads”?
Also, if huggingface is “technically” American, then fuck me, Stripe is technically European. Hell, their CEO is insanely pro europe, pro EU, and a big enabler of projects like EU Inc and lately, the Rhine Group.
I mean EU can cope all it wants, the most successful startup in Germany being a weapons company is all that you really need to know. It is sad how far these countries have fallen and I am German myself.
Germany isn’t exactly great at startups, it’s one of the worst countries in europe to create and scale one. Helsing is doing great in spite of that ecosystem, and thanks to good timing and current geopolitics.
That itself does not reflect on all of EU. Since the UK left, Germany has probably been the worst “special child” of the lot to be honest; their notaries and trade unions are the primary challengers to EU Inc for the most ridiculous reasons for example.
The $13b doesn't go to hugging face's bank acct to pay for anything like S3 egress fees... It go to hugging face's owners' Bank accounts for them to do anything else. New cohorts of billionaires and centi millionaires getting minted.
Wasn’t Huang the guy who said your $500K employee should burn at least half his salary on tokens? I don’t think Nvidia is focused on cost-effective general computing for anybody.
Maybe but they make their real money in data centers. Certainly, they want to have fingers on every trend. Owning something the Government wants to control gives you more access to trade repression of open models for more Government favors and money.
There already are a lot of forks for things they decline to implement. TurboQuant, ROCmFPX, and more. I need to set up an agent that will loop on merging them.
Nvidia is halving the production of its higher end GPUs, doubling prices and heavily segmenting the market. They don't give a single shit about individuals. One wafer that makes 10 5090s that might sell at 3000 each, or one wafer that it already sold 6 months ago for 200k to one of the incestuous AI companies it works with?
Obviously, NVIDIA is trying to own the AI development chain.
Owning HF -- the discovery and distribution channel -- is one thing, but I think the biggest threat vector is the privileged access to HF platform data, that includes HW survey info and model download pattern. This can be a borderline anti-trust case.
Also they bought the company which develops the open source slurm scheduler which is the primary and defacto standard HPC scheduler on the market. Bit of a concern to say the least
This brings back memories of the CVS/Aetna merger for me, which ended up going through of course. Hopefully the anti-trust enforcers have some experts in the ML/AI pipeline, but I wouldn't be surprised if they didn't bat an eye at this one. Hope I'm proved wrong though.
I guess this unfortunately means HuggingFace won't be "the first company to go public with an emoji instead of the three-letter ticker" as the cofounders originally intended:
"When we started the company, a running joke with my co-founders was that we wanted to be the first company to go public with an emoji instead of the three-letter ticker when you go in the NASDAQ."
-- Clem Delangue (https://unsupervisedlearning.substack.com/p/the-future-of-open-vs-closed-source)
Historically NYSE (and AMEX; thought of in this specific context as CTA) had a lock on 1-3 character symbols. NASDAQ (via UTP) had a lock on 4-6 character symbols.
For a long time you could tell where something was listed purely by looking at the length of the symbol it traded under.
This all changed in the late 2000s or so, so no longer useful information.
I honestly would leave the industry if one of the exchanges tried to bend the industry to allow an emoji in a symbol. The communication protocols essentially lock this at 8 character alpha. It would be a huge pain in the ass, for everyone, to change this just because some exchange wants to appeal to a potential listing.
Yeah, they tried to carry the suffix symbology into the ticker itself, but that fortunately died not because of some great sanctity of the symbols but because someone thought it would confuse too much with how ACT and the CTCI protocol handled security categorization.
NYSE (really the access stack that both NYSE and AMEX ran on; the name escapes me since it died back in I think ‘08) has for a long time included a completely separate field in their protocols to indicate classification (preferred, warrants, classes, when issued, etc), but CTCI just jammed it into the symbol field.
Amusingly there is plenty of precedent (link below under Nasdaq Integrated Platform Suffix and the older ACT/CTCI suffixes) for using all of the wonderful character symbols to indicate different classes of securities.
Not as common, again, as it used to be...but still exists.
Nasdaq becomes more and more like a “normal” exchange every year. Historically, they’ve always just done their own thing for their own purpose, so it makes sense.
** for those that don’t know: NASDAQ stands for “National Association of Security Dealers - Automated Quotation (service)”. It was forced into existence by the SEC. Prior to that there was only the NASD, who traded blocks of shares amongst themselves so that each individual security dealer could meet the needs of their customers. As the trading amongst themselves grew larger and larger, the SEC added progressively more regulation until finally the had to build the NASDAQ computer system, which nobody would even recognize today.
So again, they were always separate from everything else and did things that made sense according to their own needs. They were very different until they were no longer allowed to be different.
Don’t disagree there, though this has been status quo for nearly two decades now.
By that measure regional exchanges were their own beasts for a long time. The environment has definitely streamlined a ton since RegNMS was implemented and the exchanges consolidated a bit.
Even the technology stacks the current markets run are basically identical within three families of design (even the upstart markets, and even those that are not directly licensing technology from ICE, Nasdaq, or Cboe). Differentiation just doesn’t pay like it used to.
I tried for a while to push internally and amongst a few of the markets to move to ISIN, Currency, MIC but yeah…anything but that.
Honestly the problem is the ticker is too valuable advertising for the listed company, and since listings are not governed by a central regulator in the same way they are in Europe, for example, there’s always going to be this sort of friction about who is willing to bend the most to win the business.
I think ISINs being used in Europe might even predate the EU taking charge of a lot of financial market regulation.
Probably they became more popular/important specifically because tickers did not, which in turn is probably because there are so many countries/exchanges that a global exchange-driven namespace was never really feasible?
That stopped working for me on my mobile firefox (but not on my desktop) literally yesterday. It's pretty clear they're doing some kind of A/B testing.
I keep reading this about old.reddit.com and yet I keep using it without being logged in. It must be some kind of A/B testing or slow rollout? Or maybe it's regional?
The more interesting is HF turned down a $500M Nvidia investment late last year at
a $7B valuation, after passing on a $235M round in 2023 at $4.5B —
going from "we don't want a dominant investor" to a $13B full
acquisition in under a year is quite the reversal.
Oh yeah, so surprising to refuse $500M that go in the pockets of your company that is now owned in large part by the investor, but then accept $13B that go directly in your own pockets.
Reversal would be "valued at 7B then valued at nothing", this is more like "nah, we want more" then "nah, we want more" then "yes, that's what we want :)".
I don't think they passed on the 4.5 billion. They still raised it in 2023 with investors like Alphabet etc. They turned Nvidia *earlier this year* for the $7 billion valuation deal. It makes sense if they were angling for an acquisition.
its always the most virtue signaling people (sam on "openess", dario on pretty much every word coming out of his mouth, HF) that ends up doing the worst things because they always tend to extreme. Funny to see them joining the biggest corporation on earth by market cap after the every day virtue signaling of pretty much every employee working for them.
very few people can lock a vision and fight billions dollars with integrity. In tech they mostly end up shadowed. People like JB Kempf with VLC or Bellard. Maybe even Torvald or Jeremy Howard belong to this list of people who could have been way richer than they are now if they wanted to go against their visions and beliefs.
It’s a core part of the open model infrastructure. Their hardware business benefits greatly if this works really well and open models proliferate to every corner of the economy, with everyone buying GPUs with a lower capacity factor/duty cycle than the centralized ones. It also helps people across the world to collaborate on new uses for this, effectively running a massive search in the search space of what’s possible with these things, for every year (see the endless variety of quants and finetunes to fit in different cards, and bias their abilities on different tasks). More use cases pop up, some of them are killer apps, buying Nvidia’s hardware becomes more valuable at whatever price point, more people do it at higher prices, Nvidia stock chart goes up.
If Anthropic, OpenAI buy them, this org gets very different priorities, owning them ensures that doesn’t happen.
Hugging Face's internal storage system is more sophisticated now after they acquired XetHub. They have a clever way to chunk and content dedupe the data that makes it a lot more efficient to version control large files.
Xet's tech is very interesting and I greatly enjoyed their blog posts and other technical writeups[0]
But in the era of frontier models and hardware designed for fast model loading (eg: LLM on a chip) I can't imagine that this is worth so much. There's *a lot* of competition to improve Git LFS.
So while I agree with you that this plays a role I also have to believe that it's to understand model usage by competition and thus stifle it.
git lfs just dumps your bin on s3, and is abandonoware since ms bought github, since github historically hosts on aws s3 and improving it would immediately benefit amazon. gh, the maintainers of it, is the only forge that does not allow clean-up unreachable artifact from the server.
I highly doubt it, there's about a million things that only show up at scale that aren't lessons the bots can easily digest from Medium posts and bypass
There's more to than just the website. You have network bandwidth costs, security costs, infrastructure costs.
You can't just spin up a VPS and throw a few brain jar's in; the network bandwidth must be a fortune. Hosting over 700GB+ for many of the same models has storage cost too.
Accounting goodwill might be one term, but it has multiple components (trust, reputation, market share, mindshare, track record, relationships, online and offline community presence, etc. etc.)
Call me a conspiracy theorist, but I think it might have something to do with OpenAI's model hacking HF thing, especially considering OpenAI is one of Nvidia's most important customers.
They are paying for an insurance policy. Elon Musk and SpaceXAI must be incredibly interested in buying the company who was the victim of a mass hacking campaign by OpenAI. Any lawsuit, criminal investigation, or slowdown of OpenAI's model training would put OpenAI's massive data center build out, which Nvidia just backstopped, at risk.
Any DA can investigate it, they don't need Musk or some other big tech dipshit to tell them otherwise. Real crimes were committed and no charges are being pressed.
13B is a lot for an online platform that hosts weights. What's the special secret sauce that makes this so valuable? The fact that it's the go-to place for public weights?
Buying a company is very rarely about buying the tech, at least principally. It is true, as others have pointed out, that Nvidia could have "rolled their own" Hugging Face far more cheaply and probably in about the same amount of time as it will take to execute the deal end to end. That should give you a clue that the tech isn't really the target here
More than anything, they are buying a position within the ecosystem. Many of us could get a version of an app deployed in short order that implements most core HF functionality, but I am sorry to say that this is very far from the "hard part" of building a business, and this was the case even before coding agents were a thing. It's no small thing to become the first tool pretty much everyone reaches for in a particular niche, and therefore the incumbent in that niche
And there's lots of inertia keeping companies and developers on these incumbents like HF and GitHub -- see also Microsoft's play here dumping billions into a company that is basically peanuts and probably nowhere near as profitable as Microsoft normally would like. But they bought it at a time when they were trying to make Microsoft synonymous with open source, and it was a great play to that end. Likewise Nvidia wants to be synonymous with AI. Even if HF is a loss leader, the positioning is probably worth it
To a lesser degree, Nvidia probably also might like to reinvigorate its flagging cloud compute business and this could be a natural way to do that. At least TechCrunch thinks this, but I, an overconfident layperson, feel that the positioning is where most of the value is for Nvidia, and consolidating that will act as a force multiplier for that + anything else they may want to do with this space
Did you read the model hack that occured on their platform? I wouldn't exactly call them "advanced" if their security practices are anything to go by.
Code is hard but more likely it is a brand thing which is much harder to do. Nvidia for years now has tried to get a public ai model hub of sorts working. This is obviously them throwing in the towel.
It's such an obvious customer funnel they have been trying for years to make.
1. Customer googles "some model"
2. Hugging face is often top result
3. Thinks it's great
4. Buys
The customers are already on hugging face.
Acting like code is the blocker here would be very wrong. Nvidia 200% has the technical knowhow to make a hugging face platform and they'd likely make it better.
It's a narrative to pump the stock. Nothing more. Nvidia could have build out this infrastructure themselves for less than 1% of the cost, but it wouldn't have a name like Huggingface does.
They have various paid services that relate to AI—paid inference hosting; paid accounts aimed at AI development with GPU rentals [credits plus paid overages, I believe], more private storage and public storage than free accounts; and many of the community a and some other benefits on individual/team/enterprise tiers; additional paid storage above the base quotas for the paid account tiers; on demand rentals of HF managed containers on GCP and AWS, and some other things.
I’m asking more to work out what is the basis of this valuation. Why would Nvidia spend $13B for what seems to be a services that gives things away for free.
I dunno. You can argue over whether they're overpaying, but it's not like Huggingface is Clinkle. They hit $150 million in ARR this year, they have tons of runway, and according to reports, have just started to even burn the money they raised a few years ago.
I get that it's fun to be glib about the stupidity of tech elites and investors in general, but Huggingface have been pretty open about their financials and are, in my opinion as a practitioner in the field, one of the most responsible orgs in our space. They've been a pillar of open source ML for years now and have made a very positive impact on our ecosystem.
Nvidia is getting a real business generating revenue, and the center of the universe for open models. Both seem like pretty valuable attributes, from Nvidia's perspective.
Solid point. I'm sure Nvidia went into this deal expecting completely flat growth and no other benefits to their core business. Sorta like how Meta never increased Instagram's revenue from $0 and is still waiting for it to pay off that billion dollar acquisition price.
Or like GitHub, which was generating something like 200 million in ARR and had never hit profitability when Microsoft bought it for $7.5 billion back in 2018. I'm sure it has come as nothing but a happy surprise to Microsoft that GitHub generated $1 billion in 2023. They had initially penciled it in for 38 years til ROI.
With all the spending and valuations in the AI space being so reasonable and grounded in reality, sure. Huggingface will surely be exactly like GitHub and Instagram with their extremely low and stable per-user overhead, and large, extremely dedicated user bases.
I just feel like you're saying things based on a general vibe about "AI companies" but didn't pause to look up the particular company being discussed.
Huggingface reached profitability 2 years ago. They've reportedly just started to touch the cash they raised 3 years ago. They have a tiered pricing model with metered pricing on resource heavy services. Seems pretty stable?
Your point about their user base is even weirder. They play essentially the same role for the ML community that GitHub does for software engineers, so I mean, yeah I'd pretty much expect their relationship with users to be "exactly like" GitHub's for the most part? They're where everyone has published their models for the last 6 years at least, going back to pre ChatGPT and the recent AI boom. There aren't realistically any other major model hubs, certainly not with anything near their footprint.
Basic napkin math: 5% IRR means they'd only need to 4.5x their revenue to make this roughly work. If they can finance this cheaper and/or do not have better options for their cash, it's even less.
It's not too dissimilar from GitHub, but geared towards ML. They have a 9/mo pro plan for individual users for upgraded storage/usage, and an enterprise version of Hub that larger orgs can pay for. I think the enterprise has some contract minimum + 50/mo per seat. https://huggingface.co/pro
They also have inference endpoints with metered prices, and their spaces product (though i'd imagine this is a smaller portion of revenue).
I’d be curious to see how much that’s subsidized. Maybe they’re different, but when I see ML and monthly plan in the same sentence, I see zero sustainability.
Why I don’t think it’s sustainable to run a compute-intensive business on low monthly plans? If they’re like OpenAI and Anthropic, monthly plan users can spend many times the amount of money in a month than they pay, and unlike regular lower-compute SaaS businesses, overhead increases significantly with usage. That means the more users many of these services get, the more money they lose. Some surmise OpenAI was hiding the actual cost in marketing expenses to make their business look less unprofitable. Anthropic was smart enough to focus on customers most likely to be willing to pay for API pricing, so they’re in a better position. If hugging face is primarily focused on selling monthly accounts rather than token based billing which bills more as the company’s expenses increase, its not likely to ever be sustainable without significant changes.
Most of HF's revenue comes from their enterprise customers; you essentially get direct access to their MLEs (Slack) as well as their software stack, hence the per-seat cost and annual minimum contract price. In that sense they are not particularly "compute-heavy" in terms of what they "really" sell.
Yeah the people that say things like this aren’t looking for valuable companies, or to create value, or for sustainability — they’re looking for short-term growth.
Nvidia has a market cap of $5T USD today, and a decent chunk of that is due to LLM speculation.
Does Nvidia want their stock price to be at risk of being tanked by a download service being in the news? No, they want to make sure the party keeps going and is under their direct supervision, and part of that is making sure Hugging Face isn't bought by a competitor or runs out of money.
If their stock moves up more than third of percent due to this they have won... The math at these valuations get somewhat extreme. But there is some logic in it.
There is a brand and that brand is really a type of call option that is very hard to price.
If you are doing the valuation using the tools of Ben Graham it is not really going to work.
Damodaran's the Dark Side of Valuation is the text for this.
Yeah, great point. Nvidia could potentially be overpaying. Not sure how that equates to Huggingface being "a file download mirror with a couple of side features dangling off".
Absolutely none of this makes sense and the thing that amazes me is how long it has continued. Future historians will just laugh at how stupid and obvious the crash was.
While it's probably easier to say this in retrospect, they were eliminating a direct competitor to their core business. Something so advantageous it should have been blocked by regulators.
I can't see this as being as good of a purchase, especially when it's 13x the price of what was seen as an absurdly large amount back then.
I guess we may have to start paying to download models.
Or perhaps they will start throttling downloads for free users.
I don't know what they business case is, it might be to shut them down: I suspect good free models on local hardware is a threat to Nvidia's investments in OpenAI/Anthropic.
NVidia has been expending energy helping improve local models and inference platforms for them targeting NVidia GPUs; good free models that users can run locally rewards Nvidia’s investment in product lines for local inference (DGX, RTX PCs, etc), as well as—given their continued dominance in the space—the premium over competitors of their consumer and workstation GPUs.
Maybe they're trying to see how big the market actually is before considering shutting it down, maybe or getting lawyers and politicians to try and outlaw or restrict open models if they see a big enough opportunity.
This trend to vertical integration is very dangerous. We should not allow the people making tech to control the whole pipeline unless we want a permanent underclass.
Something something Apple. For what it's worth though, I agree that companies _subsuming_ others to obtain complete vertical market capture has been a very dangerous trend.
Apple isnt an analog though, in order to be a relevant analogy they would need to buy Intel, TSMC and ASML and "commit" to preserving access to other people chip manufacturing. As it is, they are guilty of reserving capacity so other producers cant access current generation tech and have to weight a cycle, which I would argue should be blocked as anticompetitive by regulators but we have a perverse definition of free markets now that defines market consolidation and monopoly as markets working instead of recognizing they are a sign that a free market has been captured and destroyed.
The open weights AI ecosystem is way too concentrated with HF. That said, it was clear they were going to either get bought or aggressively monetized at some point, Nvidia seems like it could be one of the more aligned acquirers.
I do worry about any sort of crowding out or downplaying non Nvidia-relevant quants, and about changing rules to crack down on models or datasets that for one reason or another “don’t align with their corporate values” - uncensored etc. Someone mentioned Microsoft and GitHub, they appear to me anyway to have been very hands off, I hope it’s the same model.
It's already part of Alibaba, which has its own incentives. So does kaggle with Google. Civitai is neutral but it is mostly nsfw even though they don't show it outright. Torrenting is the Best way
I could put on a tinfoil hat and say that nvidia will have some control on the flow of the open models, so if someone like the US government want to "control" and police the models like Dario was talking about then this investment might actually make sense. The HF platform can then be used as the "controlled" channel and any other site can be designated a national security risk and blocked / taken down.
This is the world we live in now. 3-4 megacorps owning everything in every major product category - eyewear, cosmetic, consumer goods, media, tech; you name it.
We need small companies worldwide, developing the things huggingface does. The us china and Europe dominate while the rest of the world sits by idly. Torrent and seed ai models. It's not piracy
Has always been this way. Big companies always seek to buy fast growing startups and unfortunately the founders of these startups mostly take the money.
Potentially horrible for monopoly reasons, but if other big acquisitions in the AI era teach us anything, developers are about to get a whole lot of free and discounted trial credits.
That’s at least a plus. I will happily burn through as much VC money as they will give me to tinker with my projects.
Current US government is pay to play. As in buy my cryptocurrency and you get a pardon or case dismissal, no backroom deal required. Payment directly. Blatant corruption sucks.
If the House or Senate turn that might actually stop or slow down. The market falling by 30% when the AI bubble eventually pops would also trigger it.
I think failing to take advantage of the charisma of both Lina Khan and Janet Yellen, and not making them public-facing economics gurus like Alan Greenspan or Larry Summers historically were, was a huge tactical mistake by Biden.
Fair, but the biggest mistake by far was failing to take charge of the immigration debate. The second biggest was his press secretary's insistence on announcing that everything was fine in the economy over and over as a distant second. Third was not resigning when it became clear that he couldn't really keep up with the job, or at least not trying to run for a second term. Virtually nothing else matters by comparison.
Fear over economic damage due to immigration is perhaps the last remaining unifying force among the American political right wing. Biden actually did a lot of good things as president -- arguably a lot more good than he did in his time as senator. But his administration was too eager to just run the federal government as a quiet meritocracy and avoid dealing with any of the hot political issues of the day. He and his administration fucked up so bad that now not only is most of that good undone, but we are in a dire existential situation, facing generational-scale damage that might be unfixable.
It's one thing that they genuinely fumbled the handling of the huge immigration/refugee waves spanning the entire continent and it took them well over a year to start coordinating a response (which they never really did apart from eventually just closing the border) -- it's another that they kept trying to insist everything was fine, there was no problem, there's nothing to see here. People were freaking out about it all over the country, and of course they were being heavily propagandized, but that's not the point. A strong and proactive White House would have made all the propaganda look stupid. Instead, it looked like the truth.
It's absolutely mind-boggling to look back on just how weak the president had to have been from 2020-2024, to somehow let the party of Jan 6 and the disastrous handling of the Covid-19 pandemic regain enough control of the political narrative to make Trump seem like anything other than a narcissistic mobster.
Yellen was objectively the dumbest Treasury Secretary ever. When everyone and their dog realized inflation was getting out of control, she thought it was transitory. She literally gets an F- as an economist.
And some former Roomba employees may have thoughts about Kahn.
Kahn was right about Roomba. Amazon was going to torpedo all the superior competition on the Amazon platform where almost all robot vacuums are sold in the US, plus as the e-commerce monopoly, Amazon was going to instantly have access to an army of cameras inside people’s homes to analyze personal information related to purchase preferences.
IMO allowing Roomba to hit chapter 11 was still a better option for the consumer than handing them to Amazon. They’re still in business as an independent competitor on the market, consolidation was successfully avoided.
Yellen, I don’t have much of an opinion on, but she absolutely wasn’t alone in that opinion (the nuance of that opinion being inflated by this hyperbole), and the treasury is a lot less involved than the federal reserve in doing anything about inflation, anyway.
This is a tangent to my first comment parent to this one, but also more related to the actual article at hand: whether it's Amazon buying Roomba or Nvidia buying Hugging Face, I have a somewhat radical (or is it?) opinion that large companies like Nvidia, Amazon, Apple, Microsoft, Coca-Cola, etc, should not actually be allowed to acquire companies. At all. under any circumstances, even if competition is healthy.
These companies are generally large enough that they do not need the competitive aid of buying an existing company and starting with that sort of structural advantage.
E.g., did Nvidia not have enough money in their bank to start a company to compete with Hugging Face? This is a company that reportedly has ~200-300 employees with investment rounds totaling $400 million. Nvidia made $31.9 billion in net income last quarter.
I look at a company like Xiaomi which just developed its automotive division in-house without resorting to buying car companies. I think our traditional business and finance mindset has an overreliance on acquisitions.
This is a lesser-of-two-evils situation. Before acquisitions became the new "meta" in Silicon Valley, the old meta was that gigantic quasi-monopolies, like Microsoft, burn money and man-years embracing, extending, and extinguishing your product.
I heard (literally with my ears, during a pseudo-dinner-thing, so this may be apocryphal, so you may have to do some spelunking through sources) that Microsoft "bought" the source code of some browser-project, for a percentage of the revenues that come from Internet Explorer. The catch was that IE was bundled with Windows for free, so a percentage of zero is zero.
A definite fact, is that when Netscape folded, the industry -- and the investors that got burned by the rapaciousness of Microsoft -- finally got in-sync enough to lobby and agitate for the antitrust lawsuit that almost broke Microsoft up. A consequence of that lawsuit is that quasi-monopolies like Meta, Google, etc, started buying promising startups instead of burying them.
I am not sure that a world where Nvidia just out-spends Hugging Face, via its quasi-monopoly-revenues, is better than the one we are currently in.
If I have to choose between two evils, I'd obviously choose the lesser one. But maybe we can do even better, and choose the absence of evil?
Maybe companies should have "weight-classes" the same way that most sports have those, to match opponents. (After all, despite both being remarkable sportists, Koga cannot defeat Ogawa, who is a few weight-classes heavier). Something like this is how France protects (or tries to) its own small business owners (I am told, they still have many small independent bookstores, despite competition from Amazon, and chain-bookstores before that).
The venture-capital does _somewhat_ balance the scales, but not by much, and it encourages the pursuit of _exits_ instead of _excellence_ (not shaming anyone for taking an exit, I am just saying that the alternative is systematically penalized -- only the very lucky or very protected can pursue excellence).
Roomba was not competitive in the market, no amount of Amazon market manipulation would have changed that. Best case scenario, Amazon would have invested in making it competitive. Worst case, their engineers would have been absorbed into Amazon's warehouse robotics projects.
Is either of those worse than what actually happened: the company is now a zombie brand for a Chinese company?
Of course Amazon would have changed that. You would go on Amazon and search for "robot vacuum" and Amazon would put iRobot at the top of the results. Review manipulation on the platform would be trivial.
Amazon could email/push notification/text customers asking for reviews of iRobot vacuums but then not do the same for competing vacuums, skewing their reviews higher (asking for reviews boosts ratings by gathering opinions from happy customers who usually don't bother writing a review). Competing brands potentially don't even have your contact information to ask for a review.
Go on Amazon right now and search for "usb cable." There's a giant banner at the top that recommends the Amazon Basics brand, three across horizontally, which on my desktop monitor takes up nearly 50% of the screen real estate. Then below it are the Anker cables that you're more likely to be looking for.
They would have almost certainly been manipulating pricing on them as well. For example, they could take the strategy of lowering the price of the vacuums to break even or sell as a loss leader, but use them as a data-gathering robot in your house to help Amazon sell more of everything else. They could make their Alexa smart home platform preferential to iRobot or lock out competing models.
Robot vacuums are a consumer goods category that is heavily skewed toward Amazon.com as the place of purchase compared to other retailers.
I think "zombie brand owned by a Chinese company" is actually preferable, yes. They still operate and sell vacuums competing with the other robot vacuums on the market, and they aren't in service as household data collection bots for a monopoly e-commerce platform.
I don't think the ownership of the company being foreign or domestic is very relevant to the FTC's goal of preserving positive trade conditions. Would we think the iRobot situation was a bad outcome if iRobot was purchased by a foreign company we view more positively like Miele? We only think of it negatively due to anti-Chinese bias. iRobot being Chinese-owned is almost certainly the best possible outcome for preserving the amount of competition in the market.
Yes, that's a very good company to be the owner of iRobot, because they are just a robot factory and not a near-monopoly e-commerce retailer.
They are essentially on equal footing with other robotic vacuum manufacturers. iRobot didn't go out of business or get absorbed into a larger company lowering competition in the marketplace.
It's also not the FTC's job to ensure that companies, especially ones with zero/trivial national security or domestic labor force value, remain under domestic ownership. Amazon itself is not really a "domestic" company, it's publicly traded. Anyone from any non-sanctioned country can buy shares of Amazon.
I spent a little time working there around 2017. Whatever you're implying my former colleagues' thoughts on the subject are (or mine, for that matter), you're probably wrong.
Now that you mention sleeping. I imagine one could do cool sleeping startups that clone something but exist only on paper. The sleeper startup is only launched the moment some ham fisted mega corp aquires the original and all the customers are looking for a way to abandon ship.
Depends who does it. If someone with the track record and budget pulls the rabbit out of the hat swiftly existing customers would at least investigate.
If you maintain a list of shortcommings or good new features it could sound like a sweet deal.
If the company was aquired to shut it down it would work even better.
Marketing is increasingly expensive. Any hype is valuable. One might as well design the product for the promotion.
True, but better nvidia than any other big tech contender. Nvidia has a very strong business incentive to make huggingface thrive, whereas pretty much everyone else has the opposite incentive.
The Government plans to regulate open source ai. Nvidea is dependent on the Government to back loans, provide property, and make laws in their favor. Now they have ownership of what the Government wants to control. A perfect wedge they can use to get more from the Government.
Why would China want to crash the AI industry? Their goal is not to damage the United States, necessarily. Their goal is to have the best domestic AI on the planet. They intend to do that through the way that they dominate every other industry: good enough quality at a much greater scale.
Surely crashing the Ai industry (in terms of reducing commercial revenue) makes it harder for the leaders to keep raising money and so keep investing in r&d to the same levels. Thus allowing competitors without access to latest American hardware to keep up.
I think this is good.. They have incentives to keep things free to keep people using their GPUs. I think that's one of the least enshittifying outcomes possible
HF is the default platform to find models. Not just ones published by big labs but also a lot of the distilled or fine-tuned versions, etc.
If Nvidia buying HF makes it tough for all the diverse models on HF, then what are some alternatives?
It seems models are the best things to be available on a Torrent platform? Of course HF is much more than just the files but perhaps the metadata can be separate and hosted on multiple community platforms.
I'd honestly prefer that. I'm usually on 5g if not 4g and pulling models is an absolute nightmare when I basically have to use HF and even with a token getting throttled. Although I have a pretty unique use case. Pulling wads of 5gb tensor files over cellular is painful.
I am on the same boat, I live in a small Himalayan village. I have 2x5G based devices and one Wireless bridge (Ubiquiti LiteBeam M5) for a local broadband. Generally I get 50 Mbps, sometimes up to 100 Mbps
i'm traveling in an RV and can always (80% of the time) get up to 3MBps, max to 300. But with cellular it's mega spotty so pulling 3-10 5GB files then losing your connection for a few seconds/minutes completely kills that files download. I've tried about 10 different keep-alive-ing type hf downloader clients and with my 64gb ram I'm usually downloading 25-32GB models and I don't even try unless I'm in sitting in a city next to a library anymore.
It's less of a pain now that I'm not in my LLM newbie phase of trying to test out 30 different models and stick with Qwen, but I couldn't even try to download qwen 3.8 for a week or two until I got back to the city.
Starlink is the obvious option and I have it on my roof but I do everything I can to not pay that $170 a month vs my $170/quarter 5g service.
I am quite skeptical that an acquisition by Nvidia will make people move somewhere else ... The network effect remains central, if you are researcher/lab/company and you want to promote your model/dataset you go to the popular platform where most of the community is. The same way most of the public repo are still being published on GitHub despite people being pissed of by Microsoft acquisition. (I you add on top of that the cost changing your workflow, not using HF library, ... it make the transition even more difficult)
I don't know anyone who "finds" models on HF. The announcements always come through Reddit, HN, Xitter, and various Discords. HF is just a place where some people bought a domain name, spun up a file server, and struck it rich. If they went away tomorrow, they'd be replaced the next day.
"Quantized models are no longer permitted on the Hugging Face platform. Reduced precision models are a safety hazard and a violation of our TOS. Click here to speak with a sales representative about our many exciting cloud hosting offerings or enterprise GPU packages."
This acquisition and the Stripe acquisition of OpenRouter are puzzling. Both HF and OR, from a technological standpoint, don't appear to have much IP that cannot be easily replicated.
I wonder how much it's worth to Nvidia just to obtain a list of who's downloading which models and for what purpose. Similarly with the Stripe acquisition of OpenRouter. In the past, it would have been valuable to obtain an audience or market share or even a productive team. However, in this new age of the surveillance state ...
America is headed towards techno zaibatsu economy.
Just a product of the dynamics of capital and power. Too much cash, Nvidia is forced to try and find ways to deploy excess capital very quickly. Most efficient way is to absorb players in emerging industries, bet on the potential for growth in new markets to help keep ROI up.
It is a great day for startups, the goal is to sell out and get rich, no?
INB4 China comes in and dismantles the American zaibatsus in 2245 like America did to Japan in 1945.
We simply need to bring back that 90% federal income tax bracket we had in the 1950s. If we had the same tax policy today, a CEO or investor would be limited to 5 million dollars a year in earnings. This is what fixed everything.
If a CEO cannot personally get richer by cutting wages, cutting staffing, and outsourcing; all of it stops. That was the secret of affordability. Don't let a thousand rich people own everythjng. Tax them so we can have millions of working millionaires instead of 900 non-working billionaire elites.
As those 1950s taxes and post 1929 financial regulations were cut in the following decades, the wealth inequality that led to the great depression has returned.
This is more a result of Clinton's failed CEO pay reform. It is what created this monster, not the tax bracket. Now, saying that, we DO need to tax these people higher. Eliminate all the ways they're able to squirm out from paying a fair share.
Marginal tax rates are meaningless because, even in the 1950s, the system was complex and can be gamed.
If you want to judge the net effect of tax policy over time, look at the percentage of GDP captured by federal receipts (the vast majority of which are taxes). In the U.S., it's averaged ~16.5%-~17.5% with occasional spikes and dips. Currently, it's very close to what it was in those 90%-marginal-rates 1950s.
I disagree on this. It's not the wealth that is the issue, it's the corruption that allows wealth to be converted into power. Citizens united is so backwards that it actually encodes the corruption as a right.
People have a right to support candidates > they can print a sign and stand on a street corner > printing signs costs money > people have a right to spend money supporting candidates.
People have a right to assemble > they can stand on a street corner with their friends > they can hold a big sign together > they can have lots of friends and form a group and print a really big sign.
We want to encourage private business > limiting liability for owners who do not participate in the business would increase access to capital > we offer corporate forms that shield investors from liability > identity of owners may be kept confidential.
People complain about the wrong thing. The problem isn't that people are allowed to support candidates with their money, buy airtime, etc.. It's that companies have secret owners...
You said "People" a lot in your post. Corporations are not "people".
Only natural persons should be able to contribute to political candidates.
Corporations can lobby, as a corporate person, just like a union or other organization, but not contribute.
They can run ads themselves, but there needs to be a much greater wall between PACs and candidate campaigns, with the previous restrictions now null and void due to lack of enforcement.
If it's okay for Corporations can run ads themselves, then your objection isn't to wealthy people supporting candidates or even them doing so secretly, but... only when the little guy pools donations and they happen to be pool donations via a corporation?
No, state's cannot e.g. discriminate on the basis of race by allowing corporations only composed of certain races. States also cannot infringe on the right to assemble or speak, by prohibiting people from supporting political candidates when they are organized as such a group.
But, generally, yes. States can require that the owners / members / corporate books / etc. of a company be disclosed publicly. If owners don't want their books disclosed, then they can forego the immunity that the corporate forms provide.
> People have a right to support candidates > they can print a sign and stand on a street corner > printing signs costs money > people have a right to spend money supporting candidates.
Individuals printing signage is not where most of the funding is going though, is it?
> People have a right to assemble > they can stand on a street corner with their friends > they can hold a big sign together > they can have lots of friends and form a group and print a really big sign.
This isn't how most of the money is being spent either, is it?
I don't know how you seem to either believe the point of the right to free assembly was to give richer corporations more sway, or be completely oblivious to the fact that that is what's actually getting people angry, not the fact that citizens want to stand with signs by the street corner. Assuming you don't have a conflict of interest leading you to that conclusion, I... don't know what to tell you.
I think your objection is fairly clear in terms of 1) you point out the difference between e.g. standing with a sign vs. more expensive options, and 2) you say "right to free assembly was to give richer corporations more sway."
Fundamentally it sounds like your complaint is that wealthy people are presumably more able to be effective with their efforts than folks who, e.g. can't afford as big of a bullhorn.
Citizens United wasn't about that. There wasn't a law saying no person shall spend more than $1k/yr supporting a candidate.
This is a completely inhuman and unamerican take. Money buys secrecy, it always has. Money is a tool, exercising speech is a right. For the Supreme Court to equate them is ahistorical, plutocratic, and terrible. You sound like you support giving corporations the right to vote as well,
Where do you draw the line between money and speech? IE, would you "simply" ban all political advertising completely - one can scream from a soapbox and that's it?
What is a corporation but people? Companies are groups of people. They're one or more owners, some managers, possibly some staff. If you take away all the people, then there's nothing there.
Democracy is built on the idea that people are equal and have equal rights. This is only sustainable if the power differential between people isn't too large.
Corporations consist of people, yes, but the power to control where the efforts of these people are directed is concentrated on very few people, giving those people a large amount of power -- so large that without any checks on their influence on government, it undermines democracy.
It's the same argument for why super-wealthy individuals are so problematic. They're literally destroying the fabric of democracy through the power imbalance afforded by their wealth.
Assets, mind share, etc. All the things that get sold off in bankruptcy proceedings.
A railroad company also has a huge amount of steel roads with cross country right of ways. You could fire everyone, and it'd still be extremely valuable. It might even be more valuable.
Even in asset-lite software land, "Atari" the name still has a lot of value, even though none of the people are there anymore. They own the right to control the things that the neurons in millions or billions of people's brains are tied to, that their habits tie them to.
Twitter, you can fire almost everyone, make the online square less pleasant for a lot of the people, the network effects truck on. People continue to use it even as they hate using it, because most everyone else is.
A corporation is a liability and pseudonym shield.
A corporation having contribution rights multiplies the otherwise imposed contribution limits on the underlying humans.
A corporation allows tax planning opportunities not afforded to the bottom 90-ish percent of the country (such as shifting income to alternate years to avoid progressive taxation, and utilizing expenses to lower that income in ways a W2 cannot)
Corporations are granted benefits that people do not get, and CU disturbs the balance of power.
Legally, the corporation itself is similar to a person and has rights unto itself, as stupid as that sounds. Those rights are different from those the individuals who run the company have.
> People complain about the wrong thing. The problem isn't that people are allowed to support candidates with their money, buy airtime, etc.. It's that companies have secret owners...
This was a major crux of Colbert’s “our lady of perpetual exemption” bit. People absolutely know about the shadowy machinations CU enabled. The lack of transparency is a major critique.
I wouldn't say CU enabled it. CU didn't address the secrecy of corporate forms. That wasn't at issue. CU was only about ~"Can people use money with their friends to support a candidate."
To say that repealing CU is the solution is to allow the critique to go unresolved, while arguing ~"People shouldn't be free to support political candidates."
We have the techno-feudalism and dystopia but none of the cool aesthetics from cyber punk or arguably even the real Zaibatsu. Nvidia isn’t cool, there’s no interesting aesthetics or back story, it doesn’t appear to have zaibatsu ambitions, it’s just riding a meme stock bubble.
In a different world I can imagine SpaceX to be the only thing that could come close, but well...
Nvidia is hedging their bets against becoming too dependent on OpenAI, Anthropic, and the hyperscalers as their only customers. If on-prem deployments of open models starts taking off in corporate America, this acquisition positions them well.
Nvidia really is best positioned to benefit from the AI wave. They are the main provider for GPUs to the cloud-based LLM companies, and their GPUs are still preferred for local models as well.
> This acquisition and the Stripe acquisition of OpenRouter are puzzling. Both HF and OR, from a technological standpoint, don't appear to have much IP that cannot be easily replicated.
I was puzzled by the comments on the openrouter acquisition saying "they're just a proxy" - they're an open marketplace where models compete head-to-head, they're quite a bit more than just a proxy.
Hugging Face has essentially become github for model repositories and I think nvidia wanted to snag that before microsoft does.
They run a proxy for LLM providers, which inevitably creates a marketplace. They’re amazon.com for tokens.
The flip side that others are pointing out is that Amazon is sticky because there’s a sprawling, physical logistics apparatus underneath. You can’t replicate amazon.com’s business without billions of dollars and a decade of building warehouses.
I don’t see where OpenRouter has that. As far as software goes, theirs doesn’t seem particularly tricky. LiteLLM does vaguely similar things, at least for organizations where managing accounts isn’t absurd overhead.
They were first, and there’s money to be made there, but what’s stopping someone else from building LibreRouter that charges a 3% or 4% fee instead of 5%? That’s where I get dubious of their valuation.
... and there is some of that two-sided market effect that (1) people who want to publish a model will publish on HuggingFace and (2) people who look for models will look at HuggingFace. Even if HuggingFace is poorly run in the future it will be hard to dislodge.
Just because a huge company could replicate an OR or HF replacement, doesn't mean by any measure that users will abandon OR/HF and flock to the mega-corp equivalent. In fact even the opposite-- users might be turned off and reticent to even try the mega-corp's..
Nvidia has a market cap of $5T, and so far today the stock is up almost 10%, so that's another $500B. Paying $13B for HF is chump change to them.
NVidia have been making lots of moves recently towards supporting open weight models and local AI, and it makes sense for them to buy HF who support the same, if for no other reason than to prevent someone else like Musk buying them just to shut them down, although I assume they have plans to do a lot more than just keep HF alive.
I think a close analogy is Github. The base infrastructure is open source and replicable, and still there's a virtuous cycle that keeps people choosing it over the alternatives.
Github definitely extended git to a far less technical audience than basic git came from. Emailing patches or connecting to others' remote hosts to pull changes was too much complexity for many customers.
Pull requests, CI platform, authentication that is not PAM etc.
OpenAI recently committed multiple felonies against HuggingFace.
Nvidia is heavily invested in OpenAI, recently guaranteeing a datacenter buildout up to $105 billion dollars.
Any reasonable criminal investigation into OpenAI's actions or negligence into this incident would hurt their reputation, their ability to raise money, and therefore Nvidia, who is invested in them.
If I was a founder of HuggingFace, I am immediately getting in contact with Elon Musk and SpaceXAI, and letting him know how that he can purchase them and sue OpenAI, this time with solid claims.
If I was particularly amoral about if I think OpenAI or Anthropic should get to AGI first, I would take this bid to Nvidia, whose entire stock price is propped up by OpenAI's over-purchasing of compute.
First mover advantage. The first big company with the most customers stays the de-facto leader of that industry/product. Later OpenRouter and HF will start building moats to keep their customers from easily leaving. That's why everyone's still on GitHub despite it blowing chunks every week. Too painful to move.
Don't see this happening. Both Nemo and TensorRT from Nvidia are heavily invested in low precision formats and higher inference throughput as well as low memory use. It's more about what happens in relation to GGUF, MLX and non CUDA-native frameworks/formats.
I really, really doubt that, and I'm a bit surprised (not too surprised, HN has gotten really cynical) that this is the top comment. I think the future nvidia most doesn't want is a small number of closed labs that run away with it, and gain power to steer a large part of the hardware spending towards nvidia's competitors, as leverage in pricing negotiations for big hardware buys. Their ideal would seem to be lots of competition in the model space, driving lots of innovation in lots of areas, at low margins for the model makers, driving use and demand for hardware way up. They want the portion of the economy working on this to go up, and that's not going to happen if there's just a few companies that can afford to build models.
VC funding (much of it from big tech). They have a freemium model and offer some pay for enterprise features, really just private repos, permissioning, etc. but not sure if it is meaningful
The history of acquisitions mothballing the acquired assets or moving them off their original mission or letting them atrophy is too stark to support your optimism. Especially when nvidia has a direct incentive to to steer the ecosystem. For example are they going to highlight and surface alternative chip designs like grok? Or will model search mysteriously not find related models?
Nvidia doesn't exactly have Oracle's reputation when it comes to acquiring companies, but given its overall hostility towards competition and open source I can't blame people for being anxious about the news.
The most important resource for self-hosting LLMs is now under the control of a company that has very markedly kept the specialized hardware outside of the broader public's hands.
You're probably right. It was mostly hyperbole, but the older I get the more I think hyperbole does eventually come to pass in situations like this. It's gradual, though, not all at once.
Natural log cynicism and any cynicism about public corporations in our late-stage capitalism world is likely to look tame a year later. Or possibly too.
I see this as NVidia placing 50% of their bets on local models as the future, which it seems may be more profitable to them than cloud (sell 100/whatever local cards, which see 40hr/week max utilization, vs one cloud card seeing 24x7 utilization).
NVidia seem like a smart company - if they want to promote this direction they are not going to cripple it by trying to limit quantized models, even though you might expect them to promote benchmarks showing the benefits of larger and less quantized ones.
It's like the smart Intel of old - support CPUs all all price points, while also promoting CPU hogging applications like OpenCV.
Ex-NVIDIA employee here who worked on inference software. When it comes to inference software and models, NVIDIA's strategy is advancing the state of the art in the open model realm. They are building software and services business for those markets that need to be competitive on their own merits, and quantization and precision tuning are techniques they use themselves constantly.
Also very silly prediction given this would dramatically lower the amount of models hosted on HuggingFace and move users elsewhere to platforms that do support quantized models (not what Nvidia wants).
Yeah. I want to be optimistic, but this feels a lot like how there used to be multiple video hosting sites and now there's just YouTube (and its copyright filters).
Unlikely, but say goodbye to uncensored and abliterated models.
These acquisitions are not healthy. They stifle competition and make it easier for governments to censor open weight models by choking off distribution points.
I am quite happy to see such a successful outcome for this team. When looking at the landscape of AI-adjacent startups, rarely do you see such a nice balance between following the hype and providing a sufficiently useful and general service that makes technology more accessible to all.
NVIDIA buying HF feels like defensive move. They don't want open models become hardware agnostic. I bet we see more 'optimized for CUDA' push in one year.
Dgx Spark and Strix Halo have very close specs and deliver similar performance. If nvidia makes their stack be more efficient with for example 50% more tockens on similar hardware specs agaist competitors, they don't need HF.
My take is that Chinese Labs, though slightly behind on the frontier (due to compute constraints) are on a trajectory to surpass Western labs (this is me speculating, reasons are better ecosystem creation on China's part and potentially better/more data environment). Qwen-3.5-122b was the king in it's category and noone came up with something better, even though many tried like poolside with laguna. Similar with 35b and 27b param models. I think poolside and HF acquisitions show us that nvidia really wants to have competitive models on the prosumer (~100-150b param size) and likely at the 300-500b as well. Together with a hardware to run them that's a good market to be in. And as the recently rumored Xiaomi AI cube shows us (together with gorgon/medusa halo and mac studios), this is a market segment that will have competition.
I do think it's a defensive move, but at first order it's defensive against OpenAI, Anthropic, and arguably Google. NVIDIA doesn't want to end up squeezed by those three as they increasingly make their own metal, etc.
Ensuring a healthy open-weight model market means ensuring continued demand for metal running in corporate data centers, bypassing any middleman. NVIDIA has a strong interest in a thriving "run your own agents" market.
They're actually aligned with Apple here. And in this market, Apple is a real competitor too, with Apple probably more consumer-centric, while NVIDIA probably more enterprise-centric.
That could be a factor, but the optimistic interpretation would be that they want to support the open ecosystem because it sells more chips.
Models are already largely hardware agnostic. It would be pretty hard to put that cat back in the bag.
I could imagine them building value-added services on top of HF to advantage Nvidia products (i.e. "run this model on NVIDIA cloud" with one-click), but in this moment it's hard to imagine how they could actively disadvantage models built to run on other platforms.
Nvidia's been pretty terrible for open source / free software. No need to quote Linus Torvalds here. They want to control what runs on their hardware. They want to you write code against their proprietary drivers and APIs, not directly against the hardware (which these days of course also contains plenty of software, but still).
Don't expect things to go differently this time around. Nvidia wants control over the software stack. Acquiring HF fits in perfectly. The play is long term.
Yes, there is no question NVIDIA wants to lock you into CUDA and their hardware. But also, they’ve consistently demonstrated the most openness when it comes to model training, datasets, and research; even before the LLM era (e.g. StyleGAN).
There’s also modelscope.cn (china’s huggingface) which is worth checking out. I would not be surprised if one day, we have to use China VPNs to download open weight models.
I'll expand on the economics somewhat. My intuition is that you can like a moat left of you in the supply chain, but dislike moats to the right of you. (I'm using left and right as I picture this horizontally drawn. It is usually called vertical integration by economists.) But free competition in your market is worst of all. Free competition right outside your moat is pretty sweet, and that's were parent is commenting on.
Nvidia probably likes that ASML is a monopolist (it's called a monopsony). The price is high and Nvidia can't scale as hard as they want to (more general: capital intensive market). This monopsony makes sure that other chip companies can't rapidly scale up and try to beat Nvidia. That there only ever was one other GPU firm (I'm prehistoric; once there were more) and they bungled it on software, is pretty sweet for Nvidia.
On the side of their customers. It would be best for Nvidia if there is free competition for the outputs generated from there GPUs. This maximizes consumer surplus and thus demand. Maximum demand for tokens, is maximal demand feeded in their monopoly. If there is a monopoly right from you, demand is curtailed, and your value is limited.
And that exactly is why you see interest from token generators for chips. Bridge that moat and gain a larger value surplus. Both NVidia and, say, China actively undercutting the token-supplier value chain is quite interesting to watch. It's like the Opium wars with us as somewhat happy customers.
In this same vein, why isn't ASML raising thousands of billions for building their own (subsidiary) chip foundries, while raising prices and starving the market (a little) for their machines.
> In this same vein, why isn't ASML raising thousands of billions for building their own (subsidiary) chip foundries, while raising prices and starving the market (a little) for their machines.
You're looking this purely through an economic lens, while in reality geopolitical factors play a huge role in what ASML can and cannot do. The US government would likely take an extremely dim view of any new external competitor popping up for their chip foundry industry (especially with all the new US plants being built or planned) and would lean heavily on their vassal/ally the Netherlands to prevent this. Unlike with China, the US has more leverage over the Netherlands[1]
The US security state and US tech giants are joined at the hip, as they have been since the beginning of Silicon Valley[1], right through the Snowden revelations through to the present day[2].
There are - see the RTX Pro 6000, which has 96 GB.
There are a few problems though, primarily, a GPU with lots of VRAM and very high bandwidth is inherently very expensive (on top of which there is also the CUDA premium); AI use cases are better served by SoCs with lower (but still high) bandwidth and more RAM.
This is not a GPU, this is a laptop SoC with CPU and integrated GPU, and knowing nvidia it will probably be even more closed than an intel CPU. You will own even less of your hardware
While nvidia 's drivers are closed source there's enough interest in running LLM's that you are not locked in using nvidia. Strix Halo chips have been around before dgx spark came out and deliver very similar performance.
When last looked at it, NVIDIA was not supporting OpenCL beyond 1.0.
Also, when running OpenCL, NVIDIA hardware disables multiple DMA engines, and allows only one memory transfer at a time to prevent OpenCL running as fast as CUDA.
Did NVIDIA finally allow open source drivers to access all parts and features of the card to allow feature parity? Last time I checked they were considering a plan for planning a solution to that.
I love your insights which enlighten my blind spots most of the time, but I didn't blame NVIDIA for OpenCL's failure. I just noted a company's choices when it comes to a competing set of libraries w.r.t. to their native ones.
Having said that, I'll try compiling a OpenCL 3.0 program in the cluster, so I can report whether NVIDIA runs this software, and if yes, how well.
Yeah, however if Intel and AMD actually delivered a working 2.0 with proper support for C++ and Fortran, maybe the OpenCL 3.0 back to 1.0 reboot would not have been needed.
Likewise SYSCL although built on top of OpenCL 3.0 primitives, is mostly Intel, which also owns CodePlay, the company that delivered the first working SYSCL compute experience, again neither AMD nor Intel (until it bought CodePlay).
I don't think bits like the GSP firmware will ever be open-sourced, but the opportunity to write better OpenCL drivers has always existed. Some of Nvidia's other proprietary driver backends (eg. GBM, Vulkan) are also decently neglected, but mostly out of disuse rather than malice. I don't think any of these things mean you don't own the hardware.
What is the support like for them? Can they be seriously considered as alternatives to Nvidia or AMD cards? I have been looking into buying a GPU, specifically the Radeon R9700 AI Pro but noticed the Intel cards too and was not sure what you make of them.
Because making new AI models is a research activity, so the group within Nvidia (or other companies) that does that activity is called a research lab, or just "lab" for short. I don't think anyone is saying that all of Nvidia is a lab (that's just shorthand I guess).
What amuses me is that “lab” is shorthand for “laboratory” and virtually no computer research happens inside a room people would typically call a lab.
It’s a little like the trend of calling developers “engineers”. There’s no actual engineering in the traditional sense but I’m sure developers think it sounds cool to call themselves that.
That’s not what I said and the snarky remark about my experience is unwarranted (I have more experience in “software engineering” than many on here have been alive)
My point was just that I just find it amusing that people call themselves engineers when the code they produce is so far removed from the level of rigour one would expect in literally any other engineering industry.
I say this as someone who also has family and friends who are actual engineers, if they built bridges and buildings to the same standards that many developers write code, then people would die.
This isn’t meant as a criticism of developers, by the way. Just an observation at the vast differences in the domains and thus the tolerance for errors in the process.
Likewise for labs. I’ve worked in AI startups and the science departments are not something one would think of when you say “laboratory”. I get why the term is used, but it’s still amusing.
I know language isn’t static. It’s something that evolves, like how a “computer” used to refer to a person rather than a thing, but that doesn’t stop me from being amused. But maybe the real issue here is I take myself less seriously than others so I have that capacity to be amused by the titles I’ve held?
Because they are mostly research departments (aka a lab) turned into a corp structure. It’s not a new phenomenon, just that until recently labs didn’t get $1T valuations so you see it more now
A few years ago everyone said _Open_AI is the the most open labs. How did that turn out? Lots of coy, deceiving actions till the whole company was turned into whatever rent seeking amoral borg adjacent shell of it's former past it is now.
"The proprietary shovel seller has some excellent tutorials on how to dig gold. Nobody else has such good step by step guides. Therefore them buying a shovel-agnostic tutorials and techniques method (that has a lot of info on using other shovels effectively) is justified."
Well if you find that obvious (I also do) then why do you not find their motives in acquiring HF onvious or that this move would be bad for the ecosystem as a whole? Cause it's all kinda the same thing.
Their (not especially great, compared to Chinese ones) models being open weight doesn't even come close to outweigh the effect of CUDA & Co being proprietary and closed.
CUDA is proprietary for a pretty understandable reason. There's no good way for Nvidia to standardize it.
They supported OpenCL when Khronos floated the idea of a GPGPU standard to manufacturers, but OEMs didn't want to design scalable hardware or sponsor the software.
Evidently we should, because Linus has been more positive about Nvidia in the last 2 years [0]. I've been using the open driver for years now, for both gaming and CUDA.
He definitely sounds more pragmatic than before, which is, in a sense, more positive.
> This is actually one of the benefits brought by AI; it has made Nvidia a good participant in the Linux kernel space. [...] Now, when Linux is so important for AI clouds, Nvidia suddenly cares very much about Linux.
Nvidia releases some of the most open open weights models, Nemotron 3, which have the full training code open, and most but not all of the training datasets.
Nvidia is a big company. They are good about some things and bad about others.
I think they really do like open weights because they make some of the best hardware for training, and the more open weights models there are, the more people are training and fine-tuning them, mostly on Nvidia hardware.
I feel like Nvidia is one of the better choices for buying Huggingface. Not perfect, but definitely far from the worst.
The worry is not that Nvidia isn’t open about their models.
The worry is that Nvidia is trying to control the way you run those models. Trying to bake CUDA assumptions into model design, and pushing the software ecosystem to be as Nvidia first as they can.
> Nvidia's been pretty terrible for open source / free software.
Their strategy for AI is pretty clear and they bank on on-premises OSS models for the busines, with their really cool open-source software:
https://www.youtube.com/watch?v=tmcn1-jFLWY
This is a really good watch and is a glimpse into what the actual future shapes up to be considering the current situation in where the OSS Chinese models successfully compete with proprietary US ones.
As a AMD GPU user, I feel as if trying to mandate CUDA only or some other way to increase NVIDIA lock in like that would be met with people leaving the platform or at lest simply working on the non NVIDIA formats away from hugging face. Though requiring a lot of space it's quite easy to spin up a competitor at least for hosting weights. And if they try some legal shenanigans then many countries outside the US will still be happy to host I am sure why not China?
The only thing I can see them being able to get away with is increasingly bending the hugging face python API and any other features of that sort they develop to NVIDIA only. I personally don't use that and don't see a reason to and I am not sure how many people do use the hugging face python library.
Hf’s python / transformers is a hot mess. It conflates so many different ideas into huge monoliths that it’s barely usable for anything other than the small snippets listed for trying out models.
They need to take a machete to all the cross coupling they’ve metastasized.
Arguably, this move will help AI open source market more. Nvidia has an incentive to make AI open source competitive with closed source. If OpenAI or Anthropic gains in market share, they will eventually gain power over hardware vendors as well, which Nvidia does not want.
Nvidia wants people and companies to go choose a free open model, run that model on Nvidia hardware. And because Nvidia can't fully control what hardware an AI model can run, Apple Silicon and AMD hardware users will benefit as well.
Hey. I worked there, and I'm no longer bound by their PR policy, so I can mention this. Also, know that the fact that I worked there doesn't make me privy to their high-level strategic decisions, this is a more look from the trenches kind of thing.
My impression I've developed in the years of working there is that Nvidia's relationship with opensource is... not intentional. They kinda suck at it because they genuinely don't know how to do it more than they want to make money out of it.
Here's an anecdotal "success story" which is also an illustration to how things might not work out well otherwise.
So, I was on the team that deals with server infrastructure. One day we get a new "feature" which was supposed to allow Slurm (the workload manager, a kind of software used to run "jobs", including eg. model training) to be deployed with distributed MySQL as a backend. The feature is all obviously written by a single developer with an enormous amount of "help" from AI. I was tasked with testing it.
Trying to figure out what it does... I realized that the "distributed" part of the feature was to be achieved by integrating with Oracle's MySQL by means of using MySQLShell (another proprietary Oracle's product). Until that point, by default, we integrated with MariaDB. Not only was it using Oracle's proprietary tool, the tool, actually, didn't support the "distributed" part of the "solution". It was pitched as the "first step on the way there".
So, I was able to push back on it, mentioning Galera, arguing that the "solution" doesn't solve the problem and will require from customers to change databases (even if they are mostly compatible... they never quite 100% compatible). And the misfeature was rolled back.
I made an effort to investigate how did we even get there, and turned out that whoever authored the "solution" had an experience of working with Oracle products, but never really tried the open-source ones. So, he didn't do a research. He just used what he knew.
Unfortunately, this is a rare win, where the evidence of disadvantages of using proprietary solution was huge and enough to turn the tide. But often it doesn't face any resistance because nobody is even aware of the problem.
If that's true, it may bode well for the future. The AI boom creates some strong incentives for Nvidia to develop an intentional strategy for software generally and FOSS specifically, and there's a chance that could influence the rest of the company in a very positive direction. Hopefully, what they learn by working with HF and having the value of their hardware products increasingly determined by their ability to run FOSS software stacks will backwash into the rest of the company, or at least make them much more aware of the problem at all levels.
I do think that they still might be a bit reticent to release fully open-source drivers, though, only because of the extent to which hardware design could be inferred from the driver source. OTOH, AI itself is making disassembling and reverse engineering binary code easier and easier, so there might not be much of a point to withholding the source in the near future.
I think this is part of an open-source play. I'm not arguing your other points, I think they're true.
They're trying to mix up the competitive landscape(that doesn't impact their bottom line, and I don't think opensource is eating their lunch), so I don't think this is fake, at least that's my initial take.
> as a force to have open weight models run better on Nvidia against the rest.
this is the crux - if nvidia makes it so that open weights end up running better on nvidia hardware than competitor's, then it's going to prevent hardware innovation and competitiveness in the entire sector.
It's like as tho General Motors buys out oil refinery to make gas for all, but the gas somehow runs smoother in GM cars.
If you don't own the customer relationship, you don't own the profit. See App store, FB.
NVidia is delivering commodity hardware to the hyperscalers, and would eventually get commodity margins (when hyperscalers make their models work on their own hardware).
Amazing article on relevant economics of squeezing vendors - actually about antitrust ad-models but:
The answer is that [advertising based] companies are an ideal test case for an increasingly common business meta-model, where companies try to create a consumer surplus at one end in order to maximize their negotiating leverage for capturing the producer surplus everywhere else in their supply chain.
It's a clever move if that's what they're doing. They're restricted in China, and are likely to face stiff competition from Chinese chipmakers in the coming years. Acquiring the largest repository of trainable models and ensuring they run better on Nvidia hardware is probably one of the few moves they have for keeping ahead of the competition. I mean, it would be terrible for the consumer, but it does make me think that NVDA is a decent investment.
Well now that they own it, they can do whatever they like. They don't necessarily have to be optimizing the models for their hardware, they could just setup preferential pipelines to funnel users to their ecosystem. That seems fairly prudent given the challenges coming their way.
We can stop with these weak excuses since AMD and Intel have done more for open source than Nvidia has, including their GPU drivers for Linux.
Nvidia on the other hand has not and the best they have done is a bunch of closed-source blobs which they do more closed source releases than the rest.
Mojo is open source and targets all GPU architectures for their compiler regardless of the vendor and nvcc targets their own (and both that and CUDA are closed source).
So this is directly an apples to apples comparison.
I'll give credit to Intel, they've always been open source friendly and I prefer to buy them because I'm not a gamer, so don't need the best.
AMD is another story. Their binary closed source blobs were even worse than nvidias for many years. So much so people used terrible performance open source tries just to avoid the headache. That they finally slopped together an open source version after they'd lost the GPU race isn't exactly noble. But as an open source supporter in general, I commend the effort still.
I care, I just don't believe you in that statement. There were "confidential nda" notes embedded in the release that Chris didn't remove until afterwards. That doesn't scream: "we're going to open source this some day!"
If it was going to "eventually" be made open source, why not do it from the start? Why not do it a year in?
From what I was told, your speculation is incorrect. I can't say anything more than that, sorry.
I don't know why you're so aggressive in tone towards me, chill out.
I am not sure you need to posit nefarious intent for this to be a bad deal for the industry at large. Basically the only provider of GPUs getting into vertical integration is a classic monopoly move and I hope regulators look very hard at this.
"That's not how citations work." (Dude on the interwebz, 2026)
But more seriously, this is my first time seeing that as well, and I'm not sure I like it. Citing an LLM is a little like citing Wikipedia to me, you cite the primary source the LLM is quoting directly, not the secondary source.
Far worse from my perspective is that it's not a fixed citation that it's not falsifiable. It's just a mutable, generalized source, which is stochastic in nature.
So much of present day feels like being back in middle school around the turn of the millenium, with classmates (and even some teachers!) new to the internet insisting that "source: internet" or "source: google" was totally fine.
It’s the formatting and formality that bother me. Say “I looked it up with Gemini,” don’t give me some weak attempt at “proper citation” to legitimize the bare minimum effort you put in.
They’re buying a brand, some employees, and some momentum — not any of their software. HF probably does have propriety goodies to make it all run efficiently, but certainly not a billion dollars worth, much less 13!
We are so used to these numbers being thrown around in the AI era that something one needs a reminder that this is 13 billion, not million. Insane exit by HF.
Was looking for this comment, the tech world has gotten completely insane with ”valuations”. I would love to hear why it was 13 and not 5. It would still be completely insane at 5 billion, but someone though they should add another 8…
Opportunity cost for Nvidia to prevent HF from going public or being sold to someone else. It's an insight into Nvidia's market prediction and what HF told them they'd do if left alone.
No company is going to be acquired for their software alone with multi-billion valuations ever again. It should be clear by now that code alone is not where the value is anymore, if it ever was.
That huge impromptu 2023 party at the Exploratorium Hugging Face did had such amazing covid-unthawing AI spring energy, and I keep thinking about it. It was clear then they had the momentum to do a lot of things, and more so now. So I was surprised by this news.
The party is a is a relatively small concern compared to the openness and github comparisons, but since no one else mentioned it, I hope something like it happens again. Or maybe that moment has passed.
I remember when people realized gaming cards could be used for general compute (GPGPU) on certain types of parallel numeric work. It was a very cool thing for many types of hackers and science and engineering students and NVIDIA went far out of their way to ensure we could never buy it.
The optimal market strategy there (as in a lot of places) wasn't "sell as much as you can". There's often a superior strategy, when (as with HPC) you have minority industry customers who are very rich and have low price sensitivity. It's to raise the price to what those special customers are willing to pay, and to drop everyone else.
What NVIDIA did was to rip out FP64 capability, systematically, from all of their consumer cards. They firewalled off "useful for GPGPU" as a differentiating feature, segmented the market, and astronomically raised the price of what (if you were looking soley at cost-to-manufacture) could have been easily affordable to any ramen student.
(It's a more obscure version of the Intel-made-ECC-memory-disappear story).
Yes, this is ironic - it was the tinkerers using CUDA on cheap graphics cards that made Nvidia stuff useful in constrained academic environments.
True about Intel and ECC, but AMD now does similar things, even with their consumer CPUs and chipsets.
These three companies now make very sure that consumer products can never canibalize those juicy data center profits - so they make sure to limit what the consumer segment can do.
The same is true for the simultaneous NVENC video encoding session limit which is artificially locked for consumer NVIDIA GPUs (see https://github.com/keylase/nvidia-patch)
For the longest time 10-bit color was only available on their professional cards. All it took was a driver update to unlock it on their consumer cards.
Same reason why GitHub was acquired for $7.5B at $250 million ARR which is 30x revenues:
VCs could not see any other reason to raise more money and Huggingface was not growing as fast as they thought to justify the valuation or the next fundraise.
So they might as well get Nvidia to save them from the VCs pressurizing them.
That doesn't make much sense to me. Companies don't just buy companies for absurd multiples out of the niceness of their heart.
In the case of GitHub, it was likely for data reasons + wanting to own where developers do work (VScode + Github).
In the case of HuggingFace, honestly not sure as I'm not familiar enough with their business. But I can assure you that Nvidia didn't buy them for 13 billion cause HuggingFace were desperate. When you're desperate, you sell for less not more.
> But I can assure you that Nvidia didn't buy them for 13 billion cause HuggingFace were desperate.
From Nvidia's side? You get to keep the shell game of where your money and hardware are going spinning on the table for a little longer. If the party stops, Nvidia loses a zero right off their valuation instantly.
And, as a side benefit, you get to place your thumb on the scale of the open-weight hosting ecosystem. And maybe even fund a Chinese Anthropic or OpenAI at a discount.
OpenAI just popped out an inference ASIC. Google is on their 8th generation of TPU. Graviton is out from Amazon. The hosting companies want Nvidia out of their finances. Full stop. Nvidia has to do something, or it's going to get swept away.
Strategically, it matters - and nvidia’s strategy is to basically own the entire industrial supply chain of the future - they have interests in their suppliers, their competitors, their users.
In this case, Nvidia wants the easiest route from:
find model -> adapt model -> optimise model -> run model
to terminate inside the Nvidia stack. This is a boon for DGX cloud.
Now what will happen to the llama.cpp performance on non Nvidia GPUs and especially on arm64 CPU chips after this acquisition? Will Apple M* chips and cloud arm64 chips (Graviton, Cobalt, Axion) become second class?
Just now I got my hands wet with local LLMs before this was announced. Can somebody from llama.cpp/ggml.ai confirm this?
We are witnessing a set of very disrupting in the industry and it is very hard to say how things will look like. AI companies buying runtimes, frameworks, editors, model routers, model hosting providers, teams behind databases... It is hard to find anyone able to reject the insane amount of money.
Very optimistic to say this will not have profound effects on the whole industry.
> Hugging Face turned down a $500 million investment offer from Nvidia late last year that would have valued it at $7 billion, the Financial Times previously reported. Hugging Face said at the time it did not want a dominant investor that could sway decisions.
So instead they sold themselves to the same investor completely ?
Nvidia don't share CUDA, don't open source their drivers, don't support capable but older hardware (forget Pascal etc), and generally charge a premium over competitors for hardware.
This acquisition will likely solidify this general stance, reduce free compute allowance for a subscription, cap downloads, push advertising, generally favour models that are Nvidia prescribed or have been sponsored, and potentially ban models and datasets that are deemed risky legally (abliterated etc).
I see no other reason why Nvidia would want this kind of vertical.
To play devil's advocate: Hugging Face was probably not profitable, and someone has to pay the bills long-term. Nvidia benefits from Hugging Face and the operating costs are pennies to them. For them it makes sense to acquire HF just to keep it running. HF shutting down or self-destructing in the search of profits would be costlier for Nvidia than just buying it now
That said, I share all your concerns. The days of a permissive hands-off HF may be numbered
Their revenue mostly comes from enterprise deals which are very profitable, and they are in a hot industry with loads of enterprise customers paying them. Storage is also extremely profitable with very fat margins at a large scale like what HF is operating at.
They had incredible revenue growth the last few years and just broke 100M in revenue. I don't know what their internal spend was , but that was almost half of their recent round in ARR. Mostly likely they were profitable or on a clear trajectory to revenue growth. Huggingface hosts a lot of data and models, but mostly static cold storage is pretty cheap tbh.
Open Libraries: CCCL (Thrust, CUB, libcudacxx), CV-CUDA (Vision), CUDA-Q (Quantum).
Open Tooling: CUDA Python bindings, NVIDIA Kernel Module (Linux driver outer layer).
Nvidia is working with Red Hat to develop the NOVA driver and with Valve to develop NVK, which will be the future open-source drivers.
Nvidia supported the Pascal architecture for 10 years. No other graphics company did that. AMD recently made the RDNA 2 architecture legacy after only 5 years.
Nvidia is that most promotes open models and contributes significantly through Nemotron and various hardware-level optimizers. I think the value has more to do with the potential dominance of the open model ecosystem.
+1 on @SillyUsername. Combined with recent acquisition of OpenRouter we see exactly what we were increasingly concerned about: tightening (chocking?) of Open Weights locally-run models. The sequence and timing of these events make the intent very clear.
Now the Open-Models crowd will try to move to some other place. But fragmentation will weaken the position. Yes, there is Civic, there are purely Chinese websites ... for those who speaks Mandarin. Which only reinforces the point.
Assuming this deal goes through, I do wonder what this means for the future of open source models. Like it's very possible the next deepseek model host it's weight on it's site first, vs treating HF as a canonical hosting site. Just my guess, but regardless we'll have to see how labs (and even countries) respond to a less neutral HF.
Vertically integrated monopolies naturally have aligned in incentives for themselves, which allows more capture which turns out bad for customers. Whether it is a monopoly is an open question.
This isn't vertical integration. This is a commoditize your complements play and that does benefit customers. Nvidia benefits from supporting the open model ecosystem, if models are a commodity the gpus become what's scarce.
Someone with financial / decision making weight their is going to ask why they are commoditizing models that run on "others" GPUs .... Since doing that makes their gpus less of the scarce resource..
Oh, I totally agree, this alone is not vertical integration, but can be a path too it, long term being able to vertically integrate undercutting others that would be on top of the chain then retracting the open model.
>Vertically integrated monopolies naturally have aligned in incentives for themselves, which allows more capture which turns out bad for customers.
Apple's devices have resulted in a great increase in quality of life for myself and family members who used to waste a lot of time with Windows drivers/BSODs/random updates/malware/etc.
It's been almost 20 years, and it's turned out OK.
1) Local inference means more general GPUs and less ASIC hardware. Only big companies can push ASIC because of the software required, meanwhile nVidia owns cuda which is the standard.
2) Local is less resource-efficient per chip (chips remaining idle much more, meaning more chips required).
3) End-customers have less bargaining power compared to hyper-scalers. Although this might change if customer hardware start behaving more like phones (SoC with everything packed in), but even then the SoC makers will likely still have less bargaining power than hyper-scalers. But then nVidia could potentially make the whole SoC too.
So overall local-inference users = higher profit margins for nvidia. They much rather have every business on the globe buy one nvidia rack (or every laptop have a beefy GPU) than have 5-10 hyperscalers buy a few hundred thousand.
The hyperscalers were stable customers buying far more expensive equipment and NVidia has also made a bank selling a lot of auxillary hardware like Mellanox to AI datacenters.
But the spending spree is probably coming to an end with the looming IPO's and NVidia is probably trying to hedge their bets by making themselves the sure bet once big-AI stops monopolizing RAM and everyone races to get their local setups.
I'm puzzled by the reactions. This is not a good thing. Yes, they're releasing more open source code and models, but they do it BECAUSE OF pressure from the community and other open source projects.
But Nvidia is a terrible open source and consumer company. They gatekeep a lot and oftentimes it's only open source in name. Outside contributions are often slow-walked or rejected if they don't align with business incentives , and leadership is retained 100% in a couple of people from a certain country.
Linus isn't wrong but at the same time NV has shipped more compute than AMD and Intel combined to consumers. The kind of performance I get out of a modest outlay never ceases to amaze me.
NV is a very different beast from all of those. I have yet to regret buying any of their products and I wouldn't touch your list with a stolen 10' pole.
Isn't it super easy for the community to just replace HuggingFace? Isn't it pretty much just a repo/index for open-weight models? Why is it even worth anything?
> Isn't it pretty much just a repo/index for open-weight models?
No, its not just a repo/index (they also have training, inference hosting, and they develop/maintain a bunch of core AI infrastructure software), and even if it was just a repo/index, replacing a bug centralized repo/index that used by an large community isn’t trivial.
Anyone could comment or speculate what this enormous valuation stems from? Sources list their revenue as $150M? If true this is likely one of the biggest valuation gap I've ever seen. IMO hugging face is not something could not be reproduced, perhaps not very easily but I see its business model akin to github's. Various github alternatives exist and so will hugging face alternatives.
Huggingface is not a product, it's a community. It's the go-to place where everyone who has anything to do with open AI models gathers. You could trivially reproduce their stack, but building such a huge AI community around a single place is probably impossible by now.
It could go either way. I think its better for Nvidia to play both open sides and closed models as their chips will be used in both. The only thing that compromises them is that there is a lot of investment they have in the closed models.
Nvidia is indeed a terrible company when it comes to open source, etc. however, as someone who has been gaming on desktop hardware since the 6xxx card days, Nvidia hardware has always worked. I switched to Linux full time since the 2XX days (maybe it was the 280 gtx?) and never had a lot of the problems everyone else got on Linux (using only the closed source drivers).
Likewise, their hardware has been rock solid and very performant for me. I bought most of my current setup second hand and they've been going strong for years now.
NVIDIA introduced programs like The Way It's Meant to be Played, optimizing major game titles specifically for NVIDIA architecture, which made competitions like AMD cards underperform in critical releases.
But they don't/didn't have the same level of market share as Nvidia, particularly in the PC gaming market. Nvidia had 65%-85% market share, and still worked with game studios to make sure their competitions failed. That's the opposite of good stewardship that's all I'm saying.
They worked with studios to optimize games for their hardware. I don’t think they went around sabotaging other companies hardware. They did what was good for them.
I think they will be, Nvidia has released open source model that also included the data it was trained on. I think they are the only ones that have done that.
When Facebook bought Instagram they basically bought a photo sharing app with 10-50 Million monthly active users. Today it has 3 Billion monthly active users. In hindsight, $1B looks a very good deal for a giant like Instagram. But it wasn't a giant back then, it was just a photo sharing app and it was really insane. So it must not be about the app or the network. Facebook paid that price to enter the mobile social media market as the market leader.
BTW Instagram raised $50 million at the valuation of $500M, just 4 days before the Facebook acquisition. %100 return of investment in 4 days, I think that's insane.
I think everyone just reads *illion and thinks 'lots of money'.
The amounts are incomprehensible at this point. I don't think anyone can conceive of 13 billion dollars accurately, including the people brokering this deal, they're just thinking of bargaining chips and weighing them in comparison to how many they have.
Nvidia is investing $1 billion in Poolside and paying $6 billion to license its technology and hire most of its engineers.
They are the elephant in the room, with their CDS sky-high. Sounds like they are opinionated on the whole AI thing, trying to drive this with open-source models, countering OpenAI using Jalapeno.
Looks zero-sum for the players.
All the while Google silently planning to get milk from all layers.
Nvidia buying Hugging Face would give them even more control over the AI ecosystem. The big question is whether Hugging Face could remain truly neutral once it’s owned by a chipmaker with plenty of competitors.
They were already pretty vocal about it, but this makes Nvidia pretty much the de facto face of open weight models.
As battle lines get drawn over duopoly vs. open weight it’ll be interesting to see what Nvidia does. They definitely want a piece of more of the stack especially as Huawei chips become more and more of an alternative to cuda.
Started from an ugly repository and ended up making history in less than 10 years, from `pytorch-pretrained-bert` to huggingface, well deserved, its fascinating to follow.
HuggingFace offers abliterated/uncensored models, which would seem to run contrary to the "AI is too powerful for regular people" narrative that the big players are pushing.
My primary concern is that Nvidia will bow to the pressure and restrict abliterated/uncensored models on HF.
Having Nvidia behind HF will now probably have a bunch of litigious entities salivating to sue them for not only allowing, but also distributing uncensored AI models that will then be used for deepfakes, porn, spam, scam, hacking, etc.
Sure that could have also been done to HF before, but I'm thinking Nvidia is a much juicier target.
Should also now be much easier for the government to just eventually force NVidia to restrict access to Chinese open models seeing as it will now become an American company that needs to obey to American law and we all know how American AI companies are lobbying for exactly that.
>Should also now be much easier for the government to just eventually force NVidia to restrict access to Chinese open models seeing as it will now become an American company that needs to obey to American law and we all know how American AI companies are lobbying for exactly that.
Using regulation to avoid having to be competitive is the American Way!
In all seriousness though, probably time to start an underground equivalent to HF.
OP said they will bow to pressure, which just means that governments will be able to control nv and get them to ban the obliterated models, implement ’safety’ controls on all uploaded models.
Nvidia’s backstop deals are now reaching $130 billion. If neocould sales collapse Nvidia can direct that capacity towards Hugging Face, and recover some of that by selling directly.
Nvidia has a strong interest in open source AI being a strong contender to proprietary models. They don't want a single AI company to win, as that company would then have enormous leverage over Nvidia, and could perhaps even erode the Cuda moat with their own chip spending.
They want the AI market to be hypercompetitive, with AI companies focusing on competing amongst themselves instead of with Nvidia on one side, and many self-hosters / small inference providers buying Nvidia GPUs for large open models on the other.
It's in Nvidia's business interest to be a good steward of Huggingface, while being a good steward of Github is at best incidental to the interests of Microsoft.
NVidia has a strong interest in profit. The only reason we are allowed to live in chip shangri-la is because they can make a profit out of it, nothing else.
All the big boy AI stuff runs on servers, which certainly aren't going to be running on Windows or Mac anytime soon. Linux _is_ what all this NVIDIA hardware is going to run on until... what exactly? FreeBSD overtakes Linux in the server space?
> Who knows what i sthe next big thing after AI. Maybe something that doesn't need Linux?
And Nvidia hardware was running on Linux before AI as well...
> And I'm not so sure that Mac is out of the equation
Mac servers exist but anyone serious about running at scale isn't using them for a number of reasons, not least of which is that Apple simply doesn't make real servers anymore...
They have the money they have the capability design and engineering in house and they are vertical. The question is whether or not they have the will, one thing that might help them come to a decision is that they now have an engineer CEO from the Apple Silicon, part of the company and not a bean counter.
HF CEO keeps posting about how great local models are running in his Mac, it would be funny to see if he replaces his MacBook with a 500W Nvidia laptop after the deal gets through.
But more importantly for business, if HF fails to use the upcoming ASIC inference chips for their ZeroGPU after the acquisition, their competitors using them might have an advantage.
For the last few months, I’ve been working on a vendor-agnostic inference library. Have 3 backends so far: legacy D3D11 for compatibility, D3D12, and Vulkan 1.3. I have reasons to believe nVidia deliberately crippling Vulkan API for their consumer GPUs. Couple examples to be specific.
nVidia driver sets quite low number for VkPhysicalDeviceLimits::maxTexelBufferElements. I don’t think that’s a hardware limit because I have D3D12 backend doing the same thing on the same hardware.
Vulkan performance is not great on nVidia. On all AMD cards I am testing, Vulkan 1.3 is the fastest backend. On nVidia however, D3D12 is faster despite tensor cores (WMMA / wave matrix multiply accumulate / cooperative matrices) are only available through Vulkan, D3D12 is using shader cores exclusively.
Yes, they could just say they're taking it towards prioritizing models that only run on one kind of equipment and making it harder to find, support or list models that run on different hardware.
The acquisition sets up corporate interests to be able to increasingly drive it.
I hope better for Nvidia and hopefully it can be cleared up, and maintained.
Context: Liz Lemon has been buying two products together because one of them creates a need for the other.
Jack Donaghy: The only thing I will be discussing with the House Subcommittee on Baseball, Quiz Shows, Terrorism, and Media is vertical integration.
Liz Lemon: What's vertical integration?
Jack Donaghy: Imagine that your favorite corn chip manufacturer also owned the number one diarrhea medication.
Liz Lemon: That'd be great, 'cause then they could put a little sample of the medicine in each bag.
Jack Donaghy: Keep thinking.
Liz Lemon: [beat] Except then they might be tempted to make the corn chips give you...
Jack Donaghy: Vertical integration.
That's not vertical integration though. Vertical integration would be the corn chip maker buying corn farms for example. I don't think there's a name for "buying makers of complementary goods".
"In microeconomics, management and international political economy, vertical integration, also referred to as vertical consolidation, is an arrangement in which the supply chain of a company is integrated and owned by that company." [emphasis mine]
"Horizontal integration is the process of a company increasing production of goods or services at the same level of the value chain, in the same industry. A company may do this via internal expansion or through mergers and acquisition" [emphasis mine]
Anything else you care to throw at the wall to see if it sticks, just go ahead and assume I disagree with you given how our interaction has gone so far.
To be fair Microsoft haven’t done as much integration with their eco system; such as integrating it with Azure DevOps as they could. And long may it continue.
Not a fan of defending GitHub, but TBH them launching GithubActions made me abandon all other CI platforms I was using in the past, I even left GitLab just for that.
A 99.5 means over one year you will need to wait about 40 hours total for the issue to be solved. What kind of high pressure crud app are you making where this is a problem?
Oh yes I can totally believe they use public and private repos for their model training. It is surprising they aren’t ahead of the curve for AI coding like Claude code, codex or cursor because of this.
I very much doubt that. Imagine the PR nightmare and potential liability if someone managed to extract from the model credentials in a private repository.
Explain to me how using OPEN source for training is theft? I've (admittedly skimmed) quite a few licenses, but I really dont remember anyone restricting reading/indexing source code?
MIT license includes: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
The argument is that AI models trained on open source should include the copyright info for all projects blended into the weights. And since they don’t, it violates the terms of the license.
It was 2018. As someone who worked at GitHub during the Microsoft era, I think Microsoft was a pretty reasonable steward of GitHub right up until Copilot started getting popular. After that, leadership stopped investing in the core product and infrastructure and either incentivized people moving into the Copilot org or just fully reorged teams into it regardless.
The load increase from AI is definitely significant, but I think with proper investment they would not be having this many issues.
This is the opening move of the end game for the current "AI" wave.
Hyperscalers and hardware manufacturers will absorb the overgrowth and hopefully (for them, sucks for us) settle at the top of the software value chain. The only way to make all the money poured into compute for the last 4 years pay for itself at any level is selling people and corporations on very inefficient software for the next couple of decades.
Not too different from what "the cloud" did to this market from 2015 or so...
> Not too different from what "the cloud" did to this market from 2015 or so...
I mean for all the inefficiencies of the cloud, it solved a lot of problems. It also created a new category of problems but rarely does any particular technology arrive as a pure boon without it's own compromises. Despite it's issues and despite how hot ASS some implementations are (looking at you Azure) I think cloud infrastructure you can at least say does solve a lot of problems for a lot of firms. I can't remotely say the same for AI.
It has a lot of uses don't get me wrong, but not nearly the number being pitched currently, and I don't know that I've seen any that I truly can't live without. And at the prices that are going to need to be charged when we turn the proverbial profit lever... I mean I'm sure tons of huge software houses where shipping is all that matters, behind things like quality, maintainability, the sanity of the development team, what have you, AI code assistants will have a lot of uses and the company will (probably) pay for it. But I think it's a stretch to say it's even remotely as good a trade as Cloud infra was.
In the handful of years since we've gotten all these supposedly revolutionary tools, software quality has already taken a gut-punch, will no sign of that slowing down, quite the opposite. And that's not even going into all the AI features being crammed into everything that few, if any users want or use. In fact the obsession with shoving AI shit into Photoshop instead of fixing any of the issues that've been present in that software since ~2009 was the straw that broke the camel's back for me and I've left Adobe behind entirely, and I know for certain based on communities I'm in, I'm far from alone in that.
Take a look at the historical developments of wage participation in global income, labor productivity growth vs wage growth, and so forth. It works very well. As long as the most capable laborers are paid well enough to go along, the rest of us have little choice. Especially after citizens united basically privatized American elections.
The inflection point is whether or not everyone else can convince the "most capable laborers" who are about to be cut from the "Most Capable Laborer Club" to join the Tang Ping Rebellion before real price discovery happens on their salaries.
No one seems to get that you have to do a general strike BEFORE they lay everyone off. It's a gambit. But either you actually were all that valuable and you can get your job back if it fails, or you weren't and you finally acted in your own self interest.
So where’s the return? Outside of annualized numbers I haven’t even heard people pretend that OAI or Anthropic are profitable. If this is all about ROI there’s sure been a lot of I for as yet unrealized R.
We can't discuss the finance of private companies so we have to wait for their IPO, acquisition by some public company, or bankruptcy to find out more.
The story written in the public numbers, from corporations or government statistics, is one of rise in factor productivity, rise in capital returns, and decline in wage participation in overall income.
I'm merely observing that it seems to be the latest chapter in the development of the capitalistic corporation.
IMO the top end goal is to allow capital to access skill without allowing skill to access capital. IF they can make these products work as advertised (big if, very very big if) the corpos can fire shitloads of low-end workers and give their middle managers access to these AI models and nothing else really has to change.
Workers lose their ability to earn a living, but OpenAI and Anthropic become the gatekeepers to effectively all productivity.
I know I sound tinfoil hat here but I don't see how else the numbers work. The only thing full-priced, profit-earning AI can possibly be cheaper than is, in my mind: as much of the workforce's salaries and cost of benefits as it can manage to offset, put together.
It's a great plan if you're a CEO who can't see beyond the next quarter's earnings call. Less so if you want things like, just pulling from a hat here, a functioning economy, a stable society, the ability for humans at large to live. But it's not like the owning class hasn't been undermining all of that for the better part of 50 years anyway.
Who (what) would all these middle managers manage? Agents? Why? If agents were so capable, they'd sure be capable of managing themselves or each other...
I mean I did word that carefully, "as much of the workforce as possible." So yes entirely possible that the middle managers get automated out too.
I genuinely don't get what the endgame here is, just AI's talking to AI's everywhere and somehow they think everything just keeps on making money I guess? But then again our current crop of oligarchs are pretty mediocre all around, so calling any of this a "plan" at all feels a stretch. Just cut costs every quarter, make the products worse, fire everyone who knows anything and sail off into the sunset making more money than any human being can actually spend in the process.
No, see, I'm making the opposite argument. This is not a bubble, this is a deliberate play by capital owners to increase returns on capital to the detriment of labor. Much like "the cloud" before. The increased capital intensity in software was inevitable and it has accelerated since 2022.
wonder if the article got updated? Currently it reads:
>The companies have not yet reached a deal, and the talks could still fall apart, the person said. Business Insider on Sunday was the first to report that Hugging Face was fielding takeover interest.
It was either they (literally) sell out or enshittify. Choose your poison. Hosting and running LLMs is an expensive business to be in. There wasn't ever going to be a good ending to this story. The original investors need to be made whole.
Not if they can't indefinitely contain ram and SSD procurement. And they can't and the Market already showed with specex that they are unwilling to float these fly by night outrageous 'investments' onto institutional holders.
Institutional holders mass revolted at spacex getting into the basket.
AI costs more than having people do the work. Q2 CFO reaction proved that.
Forgive me for newb question, but why Hugging Face is a thing at all? Couldn't models be simply distributed via torrents? And the whole aggregator thing would come down to indexing magent links published by model providers?
There's a herding effect with torrents where popular things are quick to get, unpopular things may be very difficult to get, because the majority of users delete files to save space.
I might host 3 or 4 models that I've downloaded recently, but I won't be hosting the 50 or so that I've tried in the last two years.
And who seeds it? If you're going to pay a host to seed it, they might as well just provide HTTP and let you add them as a web seed to your torrent, which we could be doing already.
But if you don't pay a host to seed it, either the host's business model won't play well with torrents, or there's no host and a torrent will rot.
The important thing about HuggingFace isn't the safetensors files, it's the READMEs and the Google search placement. It's easy to reproduce their distribution with torrents, it's very hard to then establish yourself as the default option.
It would be far more efficient to decentralize the data. But HF provides convenience, they subsidize the cost. They gained millions of users, and many enterprises. They can now sell the popularity of their platform. Nobody can buy a p2p network of people.
Or even “why would I pay for a flight when I can simply walk across the country”
It’s all about the convenience, minimising the time and effort from “looks interesting” to “running the model”.
Nvidia don’t care if you do it on their cloud, someone else’s cloud, or on your own machine - they win either way, as it further propagates the technology on which they are building their future.
hugging face is basically a real easy way to run llms. They also provide a bunch of libraries to do things like split compute across all your resources.
There are a lot problems with this post
- Only "The Information" is claiming the deal's done.
- Neither CNBC, Reuters, Techcrunch nor the Business Insider post whose title is cited do more than reference The Information's paywalled claim
- Only TC _even mentions_ the potential ~$13B deal on its homepage
- Not even a mention on Lobste.rs
I'm sure it'll be fine. As long as you have the latest 90-class card you'll probably continue have nearly full functionality from the HF libraries. (Upgrade to enterprise gear for full functionality)
The fit is theoretically good (nvidia is model agnostic) but I can see then pushing the ecosystem increasingly towards cuda and some custom nvidia software packages for inference etc etc
I'm not a fan of big-tech acquisition results either, but one benefit can be that a product continues to exist when it would otherwise become insolvent.
That specific example might be relevant to the case "I don't see any acquisition being good for the users", but not for the specific case of the HuggingFace buyout.
Workflow was already operating within the bounds of the closed Apple ecosystem. Huggingface is providing models not only for Nvidia chips but for their competitors hardware (Apple Silicon, AMD GPUs, ...).
I was not making a point. I was trying to clarify the example.
But after the answers, I do think his example is poor. Models available at HF have many purposes and will run on many platforms. Commenters here are suggesting this will no longer be the case.
Whereas the example Workflow (iOS only) -> Shortcuts (iOS only), there was no change in that regard.
The unlimited private repos for free tier would have happened anyways. You have to remember that this was around the time people were jumping ship from GitHub exactly because they didn't offer private repos for free. It was something many wanted, and they were actively seeking out other places that would give it to them.
I'm not convinced that's the case. GitHub was like that forever, they were well established and the change happened not long after Microsoft bought them. There was no global shift to gitlab instances or Atlassian as far as I am aware.
You can dislike an entity or an action and still acknowledge it also had some positive effects.
It was unreliable post acq. and before the slop-tsunami, the latter has just multiplied the underlying issue of their ipv4 only half assed azure migration.
Nvidia has already a good free offer with Nim and a lot of compute power available. Plus, they obviously have interest in spreading open models culture.
Can someone explain how this works? Huggingface serves enormous files and therefore presumably must pay huge cloud fees. As the dot com joke goes, they make a loss on every transaction, but don't worry, they're going to make it up in volume.
We keep talking about EU having to be more present in the AI race, but if the lifecycle of European AI companies is to be bought by US ones, what’s the point?
Keep an eye on Exa. With local models and niche harnesses proliferating, they're going to need a way to search without everyone having to run their own index.
Google is an obvious buyer if they could get it past regulators. A Doubleclick-level addition of the agentic stuff they're bad at to the indexing they're good at.
Nvidia is the obvious less conflicted #2
Secret third option: Cloudflare. They're already the glue for so much of this stuff.
This acquisition should be blocked (and never will sadly), they now have both the incentive and the ability to influence a platform that's supposed to be hardware agnostic (and built trust over that) toward CUDA stack
Microsoft did the exact same with github, acquired stack agnostic platform, and turned it into a copilot/azure one
Keep alive the on-prem hardware sales? Not as big part likely but still something good to have. On-prem hardware needs models to be available to be useful. So pushing those could sell more on-prem hardware.
I really wish I'd done better bookmarking back when Nvidia was talking about acquiring ARM. There were all kinds of things coming out saying, if we do this, even though we will be taking over ARM, it will transform us from the inside out. We would become a new different company, that cares about something beyond our own self interest, our own chips.
This feels like a similar leap of faith. One that is hard to believe in. Thankfully, I think Nvidia can keep the lights on here & keep this going. I don't think they have to do much, per se. But it felt implausible then to image an Nvidia that gave a shit about anyone else, an Nvidia that actually gave a flying fuck about drivers or upstream Linux or ecosystems that weren't entirely within their own control.
Similarly the upper quartile of succes here feels mostly like benevolent neglect. I think we can hope for Nvidia to just not mess up a good thing, for them to understand that this open model open ai universe hinges upon Hugging Face, and for them to pretty please keep caring about the existential risk of the hyper-ai'ers all building their own properietary models on proprietary hardware and leaving Nvidia behind some day, and HF being the hedge against being left behind.
The story is in an intermediate state right now, but as semiquaver points out, The Information is reporting it as fact. Since their reporting tends to be as reliable as it is hardwalled, we went with their claim in the title.
Please don't post unsubstantive comments to Hacker News.
No doubt you have the nucleus of a substantive comment here, but that's not enough. If you only post the shallowest top stratum of what you're thinking, other people do the same, and then we get "Laws are for poor people" and endless descending repetition. The whole point of this site is to try for something other than that.
I thin HF holds huge power in how they’ve consolidated all the open models and data, but monopoly feels like a stretch here. They are in reality a fairly small startup with lots of alternatives (all of which are much worse at this point granted) and are mostly a loss leading part of the open source ecosystem. I think it would be very hard to make a case against this on monopoly grounds, though I wouldn’t be opposed to someone trying if they thought it was possible.
HF has been a close part of my ML/AI career, coinciding exactly when I moved into this space 10 years ago. There are lot of nuances here (if the deal goes through). Some people say it's a loss for EU sovereign AI but HF is technically an American corporation. On the positive note, the founders (Julien, Thomas and Clem - all French) stem to make significant amount of money, which they are likely to pour into a new frontier AI lab in Europe. So potentially it's a big win. For Nvidia this is a great strategic play as it potentially gains control of the "AI app store" and can influence the direction of Transformers, Diffusers, PEFT and various other HF libs inits favour. At the same time Nvidia has been (somewhat paradoxically) a dominant force in actual "open source" AI and has contributed significantly via Nemotron and various optimisers close to the metal. This would likely accelerate further. Nvidia has everything to gain from having a massive open model ecosystem, instead of a consolidated market consisting of 2-3 players. Will that have impact on MLX and other contributions? We'll see!
> Nvidia has been (somewhat paradoxically) a dominant force in actual "open source" AI
Nothing paradoxical about it, open source AI use raises demand for nvidia's chips too.
And I would say it's actually a more secure future demand channel than the hyperscalers. Openai and co can build their own chips, so they won't buy from NVidia. But they probably won't sell them to somebody else, so everyone who wants to run their own install (and can, not the least because of HF), will buy Nvidia.
Locking the next generation of programmers into CUDA
It was Nvidia’s competitors’ job to ensure this never happened but hardware companies rarely value the software stack as much as they should have. AMD screwed up several times to build a similar tool and Intel did not manage to create a proper programming model for their vector instruction sets despite having some promising internal efforts. Cuda allowed AlexNet to usher the deep learning era, written by university researchers. The flash attention implementation allowed quadratic attention to have reasonable memory requirements again written by a university professor and used by everyone. If I were to complain about Nvidia, I would complain about them abandoning the personal computing track for datacenter profits, definitely not about pushing Cuda.
Translating CUDA kernels to ROCm (or any other ecosystem, tbh) is going to become trivially easy with AI. Not saying that code is the only glue that Nvidia has when it comes to their ecosystem, but it’s certainly a large part of it.
It's not that difficult at the moment. Don't know why you would need an LLM to translate between two nearly identical language extensions.
Optimization is different, but that's not really a translation level task.
> which they are likely to pour into a new frontier AI lab in Europe
HF was.. a hub to download models and some of the worst source code in the space that contributed to huge amounts bugs that did a lot of downstream damage. Go ahead and read their blog by their CTO on how they don’t believe in DRY and then implemented DRY in the worst way imaginable with unnecessary code generation.
Their BLOOM model was a joke and dead on arrival.
But yea these guys are definitely going to be the frontier of EU AI.
They’ve provided insane value to the ai community. Imo is there really any obvious way to standardize model/preprocessing/inference/training/rl recipes across the space of frankenstein model family/architecture/modality combinations? It’s not even clear to me that the current frontier would be where it is today without HF doing what they did how they did it. Where else were people widely sharing datasets w that ease of reuse/redistribution, or sharing their retuned models etc? Would there even be as much interest/tinkerers today?
Their strength was the ability to keep at the very fast moving AI frontier.
When a new model is released they have been able to have a working implementation days later, not months when the model was redundant. And often it's much more usable than the one-off, unmaintained, research code written in a very fragile environment.
BLOOM was a decent fully open and very large model for its time, and a huge coordination effort. It was around the same time as another "joke", OPT, but that gave Meta the knowledge that let them build Llama. Huggingface didn't have the money to compete in that race, but I'd bet it helped them stay at the frontier of AI software.
Google could have owned this space; they had TensorFlow hub, but it was too hard to use and too locked down. Huggingface made it easy to run and train transformers, and got the timing just right.
I'm glad someone is trying to build truly open models (along with the great work at Allen AI), because the likes of Meta and Alibaba are only going to release weights as long as it suits their business.
> But yea these guys are definitely going to be the frontier of EU AI.
Yeah probably more like the frontier of early retirement.
You mean DRY as in the LLM sampling technique "Don't repeat yourself"?
I wonder if they had been more pure technically, would have they been acquired for more than $13 billion? Less? Acquired at all?
A good reminder that moving fast and getting product fit >>>>> code quality
It has to be a bell curve doesn't it.. I am too much of a perfectionist... Then again, my llms constantly claim that I am doing things that are beyond the SOTA. Even my own mom lost hope.. Still haven't shipped a single thing... haha.
(half joke aside, it is finally coming in a couple days.. which I have been saying for quite some time to the extent that my peeps don't even trust me anymore.. 3 things are coming and it is genuinely research grade apparently, for the amount of research I am aware that is released publicly. I really don't know how people ship things, the tooling I see is terrible, or maybe I have NIH syndrome...)
> HF has been a close part of my ML/AI career, coinciding exactly when I moved into this space 10 years ago.
This is wildly offtopic, but: what's it been like for you?
A niche seemingly academic interest in 2016 has exploded into revolutionary practicality.
I bet you have some insights and good stories.
I don't get the EU reference in any sense:
"The company was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf in New York City, originally as a company that developed a chatbot app targeted at teenagers. ..." Wikipedia
Besides that: which EU and sovereignty doesn't really rhyme, given data protection, energy costs, AI restrictions and no vital start up scene at all.
Mistral is heavily state funded via Banks that are predominantly owned by the French state, so I don't get it.
Also name one global success that doesn't came from US? China? Well, second place maybe, but second in any sense.
Nevertheless, kudos to huggingface. Not only to the founders, but to the ecosystem and I guess it got harder by the day to finance all the hosting and only hope for the future, that Nvidia will help HF to thrive, at least not put burdens on them.
GitHub is still alive, and hope that HF will benefit from more AI power.
Nvidia doesn't have any disadvantages in my playbook, because hardware wise, there is no one to beat them in any regard and Apple will always stay nichy.
So well played - hopefully.
It could be worse or even a shut down otherwise, who knows. So for me it sounds cool and I am glad that EU isn't involved in any regard.
As the AI Act demands full disclosure under really easy to match requirements into your inner workings, this is quite the opposite of freely sharing information.
China as “second place in any sense” ignores reality.
TikTok: achieved global cultural and algorithmic dominance.
DJI: controls roughly 70% of the global consumer and commercial drone market.
CATL: The world’s largest EV battery manufacturer.
BYD: Surpassed Tesla in total electric vehicle production volume.
Shein & Temu
The list goes on…
Europe will talk tepidly about reusable rockets, China will develop reusable rockets.
The list goes on for products and services they cloned from western innovation. China didn't get there first in any of the categories you listed. Of course, people would rather spend less than more, disregarding the quality and longevity of the product.
Paying pennies on the dollar for a BYD vehicle sounds great when all you consider is the initial sticker price. The real cost is what happens after you buy the disposable car and own it for a decade.
So yea. Second place is the reality and it is also true for AI models, and the hardware needed to run them.
Also, congratulations on landing a rocket 11 years after the US.
Took long enough.
From where I’m sitting in Europe, Tesla feels like the disposable car. Gatekeeping repairs and parts and more quality defects needing post shipment corrections than other brands.
To take a concept and refine it to reach mass production is success. It is what made the US what you believe it is today and it is what is creating a healthy supply chain in China. Just look at the challenges of Destin of Smarter Every Day[1] when producing a grill scrubber using only US suppliers and materials.
A “Made in the USA” label is no guarantee of superior design or manufacturing quality to me but if Japan is mentioned I have a greater confidence in the quality of the product.
[1]: https://www.smartereveryday.com/smarterscrubber
A global non USA success? Plenty.
You might want to remove your pink USA glasses and look around.
Spotify good enough for you?
Has Spotify made money yet?
Sorry but you're talking absolute nonsense, Europe has no global successes?
How about...
SAP (Germany) - Most of the Fortune 500 run on their software.
Spotify (Sweden)
Novo Nordisk (Denmark) - most of America is taking their drugs.
Airbus (France) - Has out competed and out delivered Boeing for years.
Ericsson and Nokia (Finland and Sweden) - Most of American telecom systems use tech from them, essentially the western alternative to Huawei in telecom networking.
Adyen (Netherlands) - One of the worlds largest payment processors, processes most of American big tech payments.
ASML (Netherlands) - Responsible for building effectively every modern chip in the world outside of China.
Maersk (Shipping and logistics)
Siemens (Industrial Tech)
Infineon (Semis)
And there are so many more I'm missing btw. It's funny how incredibly biased you are, but the reality is that Europe and the USA are totally dependent on each other, tech wise.
If every European company which the US is dependent on immediately stopped trading with the US, the US would collapse as a country. And yes, the opposite is true also. But it was you who argued that Europe effectively has no successful companies, what rubbish.
Lego (Denmark).
They may not be a financial and industrial juggernaut like the others listed, but cultural significance doesn't have to be all about money.
If SAP appears in a list of successes then clearly EU is fucked.
That's an embarrassing example that shouldn't have been at the top, but most of the rest are good.
Yet on most metrics IBM is a success.
SAP isn’t a company to be crazy proud of, but it doesn’t make it not a success nor does it mean “EU is fucked”.
May I remind you that in the US, Facebook is in that same list of top successes? Have you ever heard the phrase “the top minds of this generation of Americans are all working on ads”?
Also, if huggingface is “technically” American, then fuck me, Stripe is technically European. Hell, their CEO is insanely pro europe, pro EU, and a big enabler of projects like EU Inc and lately, the Rhine Group.
I mean EU can cope all it wants, the most successful startup in Germany being a weapons company is all that you really need to know. It is sad how far these countries have fallen and I am German myself.
Germany isn’t exactly great at startups, it’s one of the worst countries in europe to create and scale one. Helsing is doing great in spite of that ecosystem, and thanks to good timing and current geopolitics.
That itself does not reflect on all of EU. Since the UK left, Germany has probably been the worst “special child” of the lot to be honest; their notaries and trade unions are the primary challengers to EU Inc for the most ridiculous reasons for example.
But the talent is here.
Well congrats to Clem and the team. I remember when huggingface was doing things like coreference resolution models on spacy.
I hope nvidia does right by the community.
Edit to add: $13B should cover the S3 egress fees for a couple months :D
Totally, and as long as they don't turn on the AWS NAT Gateway, they'll be just fine.
The $13b doesn't go to hugging face's bank acct to pay for anything like S3 egress fees... It go to hugging face's owners' Bank accounts for them to do anything else. New cohorts of billionaires and centi millionaires getting minted.
I think he was telling something called a joke. It's funny because S3 is expensive and they just got some money.
> billionaires and centi millionaires
I think you mean hecto-millionaires.
I think you mean people whose net worth, expressed in millinaires, exceeds 10^11
I think you mean Dodecahedrillionaires
Decitrillionaires
I think you mean mibionaires
They need to switch to egrees free cloudflare R2!
Cloudflare R2 has free egress only until Cloudflare’s enterprise sales team sets its sights on your wallet :)
I wonder if Cloudflare would find a cause to exclude them because I can't imagine the transfer amounts this would generate.
Nothing is free on cloudflare enterprise plans and they will make you move to enterprise once you start using enough services.
I'm using Cloudflare Enterprise and the R2 add-on is provisioned where we only pay for storage, not egress.
Ah yes Spacy, good times :)
Remember just 6 months ago that "Ggml.ai joins Hugging Face to ensure the long-term progress of Local AI" (https://news.ycombinator.com/item?id=47088037)
(Ggml.ai is llama.cpp.)
Curious if the “I consider HuggingFace more "Open AI" than OpenAI” sentiment in that top comment will still apply with NVIDIA as the boss now...
Nvidia is promoting "unmetered intelligence". Jensen wants everyone to have a spark dgx with an nvidia chip in their home.
Wasn’t Huang the guy who said your $500K employee should burn at least half his salary on tokens? I don’t think Nvidia is focused on cost-effective general computing for anybody.
Maybe but they make their real money in data centers. Certainly, they want to have fingers on every trend. Owning something the Government wants to control gives you more access to trade repression of open models for more Government favors and money.
NVidia has reasonable incentives to keep things open indefinitely, it wants people to use it's GPUs
Issue is that llama.cpp is the best way to run models on hardware that isn't nvidias.
A lot of llama.cpp contributions come from the community and ecosystem, like Unsloth. If something goes awry, I fully expect lots of forks.
There already are a lot of forks for things they decline to implement. TurboQuant, ROCmFPX, and more. I need to set up an agent that will loop on merging them.
Except when they have less than 16 gb of ram?
Nvidia is halving the production of its higher end GPUs, doubling prices and heavily segmenting the market. They don't give a single shit about individuals. One wafer that makes 10 5090s that might sell at 3000 each, or one wafer that it already sold 6 months ago for 200k to one of the incestuous AI companies it works with?
It'd be really nice if I could use my egpu 4090 on my macbook pro..
For LLM workloads this might help? https://docs.tinygrad.org/tinygpu/
Interesting, I've never seen this, thanks
Obviously, NVIDIA is trying to own the AI development chain.
Owning HF -- the discovery and distribution channel -- is one thing, but I think the biggest threat vector is the privileged access to HF platform data, that includes HW survey info and model download pattern. This can be a borderline anti-trust case.
If the acquisitions of late tell us anything at all, it's that Nvidia wants to be a vertical AI company, not a hardware or gaming company.
Also they bought the company which develops the open source slurm scheduler which is the primary and defacto standard HPC scheduler on the market. Bit of a concern to say the least
This brings back memories of the CVS/Aetna merger for me, which ended up going through of course. Hopefully the anti-trust enforcers have some experts in the ML/AI pipeline, but I wouldn't be surprised if they didn't bat an eye at this one. Hope I'm proved wrong though.
Why will this be an antintrust case but msft owning github is not?
There will be no antitrust cases unless it's a shakedownx
I guess this unfortunately means HuggingFace won't be "the first company to go public with an emoji instead of the three-letter ticker" as the cofounders originally intended:
Little bit of a “the more you know” moment.
Historically NYSE (and AMEX; thought of in this specific context as CTA) had a lock on 1-3 character symbols. NASDAQ (via UTP) had a lock on 4-6 character symbols.
For a long time you could tell where something was listed purely by looking at the length of the symbol it traded under.
This all changed in the late 2000s or so, so no longer useful information.
I honestly would leave the industry if one of the exchanges tried to bend the industry to allow an emoji in a symbol. The communication protocols essentially lock this at 8 character alpha. It would be a huge pain in the ass, for everyone, to change this just because some exchange wants to appeal to a potential listing.
NASDAQ at one point wanted to have "special characters" e.g. *()/ etc in ticker names too.
EVERYONE said it was a bad idea but they kept pushing it. Repeatedly.
Eventually, smarter heads prevailed and they got rid of the idea.
Yeah, they tried to carry the suffix symbology into the ticker itself, but that fortunately died not because of some great sanctity of the symbols but because someone thought it would confuse too much with how ACT and the CTCI protocol handled security categorization.
NYSE (really the access stack that both NYSE and AMEX ran on; the name escapes me since it died back in I think ‘08) has for a long time included a completely separate field in their protocols to indicate classification (preferred, warrants, classes, when issued, etc), but CTCI just jammed it into the symbol field.
Imagine how much stuff breaks if they allowed a comma.
Couple examples in my Twitter thread on FinTech outages that were basically that: https://x.com/alexpotato/status/1215876962809339904
Stock ticker: "BIGCO'; DROP TABLE TRANSACTIONS"
> 8 character alpha
Good thing “xn--zp9h” fits, then.
Amusingly there is plenty of precedent (link below under Nasdaq Integrated Platform Suffix and the older ACT/CTCI suffixes) for using all of the wonderful character symbols to indicate different classes of securities.
Not as common, again, as it used to be...but still exists.
https://www.nasdaqtrader.com/trader.aspx?id=CQSsymbolconvent...
Nasdaq becomes more and more like a “normal” exchange every year. Historically, they’ve always just done their own thing for their own purpose, so it makes sense.
** for those that don’t know: NASDAQ stands for “National Association of Security Dealers - Automated Quotation (service)”. It was forced into existence by the SEC. Prior to that there was only the NASD, who traded blocks of shares amongst themselves so that each individual security dealer could meet the needs of their customers. As the trading amongst themselves grew larger and larger, the SEC added progressively more regulation until finally the had to build the NASDAQ computer system, which nobody would even recognize today.
So again, they were always separate from everything else and did things that made sense according to their own needs. They were very different until they were no longer allowed to be different.
Don’t disagree there, though this has been status quo for nearly two decades now.
By that measure regional exchanges were their own beasts for a long time. The environment has definitely streamlined a ton since RegNMS was implemented and the exchanges consolidated a bit.
Even the technology stacks the current markets run are basically identical within three families of design (even the upstart markets, and even those that are not directly licensing technology from ICE, Nasdaq, or Cboe). Differentiation just doesn’t pay like it used to.
Agreed. Even LTSE is just running the MEMX stack.
Anything but ISINs, I guess...
I tried for a while to push internally and amongst a few of the markets to move to ISIN, Currency, MIC but yeah…anything but that.
Honestly the problem is the ticker is too valuable advertising for the listed company, and since listings are not governed by a central regulator in the same way they are in Europe, for example, there’s always going to be this sort of friction about who is willing to bend the most to win the business.
I think ISINs being used in Europe might even predate the EU taking charge of a lot of financial market regulation.
Probably they became more popular/important specifically because tickers did not, which in turn is probably because there are so many countries/exchanges that a global exchange-driven namespace was never really feasible?
It doesn't. Only 5 of those characters are in the alphabet.
Everyone's got a noble goal until they get a buyout offer promising to make them a billionaire
Edit: Just discovered via this post that hn posts, like the exchanges, filter out emoji
Well, yeah. I also wouldn’t like to explain to my family why my emoji is more important than being set for life.
$100M+ from the IPO isn't enough to being set for life, it has to be $1B+ from the buyout?
It's not just emoji. Using hackernews is much worse than old.reddit.com used to be.
Ironically enough, reddit recently killed off old.reddit; you now have to log in, which defeats the point of old.reddit.com totally.
Or use the addon Old Reddit Redirect, which still works as of 2026-08-27.
https://addons.mozilla.org/en-US/firefox/addon/old-reddit-re...
That stopped working for me on my mobile firefox (but not on my desktop) literally yesterday. It's pretty clear they're doing some kind of A/B testing.
I keep reading this about old.reddit.com and yet I keep using it without being logged in. It must be some kind of A/B testing or slow rollout? Or maybe it's regional?
Even the eggplant?
Especially the eggplant.
“Yes, I hear you Clem Fandango!”
The more interesting is HF turned down a $500M Nvidia investment late last year at a $7B valuation, after passing on a $235M round in 2023 at $4.5B — going from "we don't want a dominant investor" to a $13B full acquisition in under a year is quite the reversal.
Well, if they didn't want a dominant investor, they didn't get one, they got acquired.
Money from a dominant investment doesn’t accrue to the founders. Money from an acquisition does.
Sounds like it was just too much money for the stakeholders to refuse
Yea, my bet is that there is quite a long list of money bags sitting behind the leadership team that will weigh in if the offer is juicy enough.
Double or nothing
Oh yeah, so surprising to refuse $500M that go in the pockets of your company that is now owned in large part by the investor, but then accept $13B that go directly in your own pockets.
Seems the opposite of a reversal to me.
Reversal would be "valued at 7B then valued at nothing", this is more like "nah, we want more" then "nah, we want more" then "yes, that's what we want :)".
I don't think they passed on the 4.5 billion. They still raised it in 2023 with investors like Alphabet etc. They turned Nvidia *earlier this year* for the $7 billion valuation deal. It makes sense if they were angling for an acquisition.
This is the article you are referring to is this but your facts are wrong: https://techcrunch.com/2026/08/24/hugging-face-reportedly-in...
Everyone's got a price and NVidia found it
its always the most virtue signaling people (sam on "openess", dario on pretty much every word coming out of his mouth, HF) that ends up doing the worst things because they always tend to extreme. Funny to see them joining the biggest corporation on earth by market cap after the every day virtue signaling of pretty much every employee working for them.
very few people can lock a vision and fight billions dollars with integrity. In tech they mostly end up shadowed. People like JB Kempf with VLC or Bellard. Maybe even Torvald or Jeremy Howard belong to this list of people who could have been way richer than they are now if they wanted to go against their visions and beliefs.
Soo, what are they buying exactly?
Can I setup a forgejo instance, upload a bunch of open source models to it and get bought out for $13bln?
I fail to see the point of this. Their inference hosting is a joke (I don't think I ever had a working response from a "try this model" form).
Their brand alone surely is not worth this much.
So what are they paying for?
I worry the answer is, for control over who is allowed to distribute the weights. Nothing else.
It’s a core part of the open model infrastructure. Their hardware business benefits greatly if this works really well and open models proliferate to every corner of the economy, with everyone buying GPUs with a lower capacity factor/duty cycle than the centralized ones. It also helps people across the world to collaborate on new uses for this, effectively running a massive search in the search space of what’s possible with these things, for every year (see the endless variety of quants and finetunes to fit in different cards, and bias their abilities on different tasks). More use cases pop up, some of them are killer apps, buying Nvidia’s hardware becomes more valuable at whatever price point, more people do it at higher prices, Nvidia stock chart goes up.
If Anthropic, OpenAI buy them, this org gets very different priorities, owning them ensures that doesn’t happen.
Hugging Face's internal storage system is more sophisticated now after they acquired XetHub. They have a clever way to chunk and content dedupe the data that makes it a lot more efficient to version control large files.
Xet's tech is very interesting and I greatly enjoyed their blog posts and other technical writeups[0]
But in the era of frontier models and hardware designed for fast model loading (eg: LLM on a chip) I can't imagine that this is worth so much. There's *a lot* of competition to improve Git LFS.
So while I agree with you that this plays a role I also have to believe that it's to understand model usage by competition and thus stifle it.
[0] - https://huggingface.co/docs/hub/en/xet/overview
git lfs just dumps your bin on s3, and is abandonoware since ms bought github, since github historically hosts on aws s3 and improving it would immediately benefit amazon. gh, the maintainers of it, is the only forge that does not allow clean-up unreachable artifact from the server.
Surely you could now vibe code such system for under $1,000.
I highly doubt it, there's about a million things that only show up at scale that aren't lessons the bots can easily digest from Medium posts and bypass
There's more to than just the website. You have network bandwidth costs, security costs, infrastructure costs.
You can't just spin up a VPS and throw a few brain jar's in; the network bandwidth must be a fortune. Hosting over 700GB+ for many of the same models has storage cost too.
> Their brand alone surely is not worth this much.
HF has become the front runner in open model hosting. They have a lot of trust from the wider community. That's gotta count for something.
Lawyers (and bean counters) call it 'goodwill'. One word.
Accounting goodwill might be one term, but it has multiple components (trust, reputation, market share, mindshare, track record, relationships, online and offline community presence, etc. etc.)
I think they should worth much much more than this
Call me a conspiracy theorist, but I think it might have something to do with OpenAI's model hacking HF thing, especially considering OpenAI is one of Nvidia's most important customers.
They are buying the user base.
>So what are they paying for?
They are paying for an insurance policy. Elon Musk and SpaceXAI must be incredibly interested in buying the company who was the victim of a mass hacking campaign by OpenAI. Any lawsuit, criminal investigation, or slowdown of OpenAI's model training would put OpenAI's massive data center build out, which Nvidia just backstopped, at risk.
Any DA can investigate it, they don't need Musk or some other big tech dipshit to tell them otherwise. Real crimes were committed and no charges are being pressed.
DAU
Sometimes I wonder if anybody on this website has ever actually done professional software engineering at scale. What a ridiculous take.
13B is a lot for an online platform that hosts weights. What's the special secret sauce that makes this so valuable? The fact that it's the go-to place for public weights?
It isn't an awful 'surface level take'.
I'm not that familiar either, and so had same question.
I thought they just hosted other peoples models. So why the value of 13B?
Buying a company is very rarely about buying the tech, at least principally. It is true, as others have pointed out, that Nvidia could have "rolled their own" Hugging Face far more cheaply and probably in about the same amount of time as it will take to execute the deal end to end. That should give you a clue that the tech isn't really the target here
More than anything, they are buying a position within the ecosystem. Many of us could get a version of an app deployed in short order that implements most core HF functionality, but I am sorry to say that this is very far from the "hard part" of building a business, and this was the case even before coding agents were a thing. It's no small thing to become the first tool pretty much everyone reaches for in a particular niche, and therefore the incumbent in that niche
And there's lots of inertia keeping companies and developers on these incumbents like HF and GitHub -- see also Microsoft's play here dumping billions into a company that is basically peanuts and probably nowhere near as profitable as Microsoft normally would like. But they bought it at a time when they were trying to make Microsoft synonymous with open source, and it was a great play to that end. Likewise Nvidia wants to be synonymous with AI. Even if HF is a loss leader, the positioning is probably worth it
To a lesser degree, Nvidia probably also might like to reinvigorate its flagging cloud compute business and this could be a natural way to do that. At least TechCrunch thinks this, but I, an overconfident layperson, feel that the positioning is where most of the value is for Nvidia, and consolidating that will act as a force multiplier for that + anything else they may want to do with this space
Did you read the model hack that occured on their platform? I wouldn't exactly call them "advanced" if their security practices are anything to go by.
Code is hard but more likely it is a brand thing which is much harder to do. Nvidia for years now has tried to get a public ai model hub of sorts working. This is obviously them throwing in the towel.
It's such an obvious customer funnel they have been trying for years to make.
1. Customer googles "some model" 2. Hugging face is often top result 3. Thinks it's great 4. Buys
The customers are already on hugging face.
Acting like code is the blocker here would be very wrong. Nvidia 200% has the technical knowhow to make a hugging face platform and they'd likely make it better.
It's a narrative to pump the stock. Nothing more. Nvidia could have build out this infrastructure themselves for less than 1% of the cost, but it wouldn't have a name like Huggingface does.
It's a customer funnel. They've been attempting a similar product for years and nobody cares.
Eventually they can close it off to seamless integration with AMD, Intel, and any other upstarts that threaten them.
What is the business model of hugging face? My understanding was they were basically just a file hosting platform.
They have various paid services that relate to AI—paid inference hosting; paid accounts aimed at AI development with GPU rentals [credits plus paid overages, I believe], more private storage and public storage than free accounts; and many of the community a and some other benefits on individual/team/enterprise tiers; additional paid storage above the base quotas for the paid account tiers; on demand rentals of HF managed containers on GCP and AWS, and some other things.
Here is an employee of HF at a time answering how do they make money, supposedly [1]
> We make money via compute credits + Enterprise Hub + HF Pro subs [...]
I guess this plus custom inference deployments, external inference providers, partnerships with the big cloud AWS, Azure, etc.
[1] https://x.com/reach_vb/status/1928050126498713706
If GLM-5.3 was truly trained and ran on Chinese chips, we'll have to ask what the business model of Nvidia itself is soon :)
Isn't this pretty much the model for any tech company? Rush to get MVP released, stoke the hype, cash in on FOMO.
Having an account of practically every software engineer remotely interested in AI....Profit
Didn’t we just witness it? Become a critical ecosystem player then get acquired based on the value of that position.
I’m asking more to work out what is the basis of this valuation. Why would Nvidia spend $13B for what seems to be a services that gives things away for free.
Talking about profit is so passé in the new economic paradigm. The rules have changed— it’s about how much a company is worth. Get with the times.
–Some guys in every bubble I’ve witnessed.
I think Russ Hanneman calls it a "pure play" type of company. He put radio on the internet, so he would know.
Reference: https://youtu.be/BzAdXyPYKQo?si=TD0dU3Zim5o_zaE4
I dunno. You can argue over whether they're overpaying, but it's not like Huggingface is Clinkle. They hit $150 million in ARR this year, they have tons of runway, and according to reports, have just started to even burn the money they raised a few years ago.
I get that it's fun to be glib about the stupidity of tech elites and investors in general, but Huggingface have been pretty open about their financials and are, in my opinion as a practitioner in the field, one of the most responsible orgs in our space. They've been a pillar of open source ML for years now and have made a very positive impact on our ecosystem.
Nvidia is getting a real business generating revenue, and the center of the universe for open models. Both seem like pretty valuable attributes, from Nvidia's perspective.
150 million a year? Why, at that rate NVidia will make their money back in just 86 years.
Solid point. I'm sure Nvidia went into this deal expecting completely flat growth and no other benefits to their core business. Sorta like how Meta never increased Instagram's revenue from $0 and is still waiting for it to pay off that billion dollar acquisition price.
Or like GitHub, which was generating something like 200 million in ARR and had never hit profitability when Microsoft bought it for $7.5 billion back in 2018. I'm sure it has come as nothing but a happy surprise to Microsoft that GitHub generated $1 billion in 2023. They had initially penciled it in for 38 years til ROI.
With all the spending and valuations in the AI space being so reasonable and grounded in reality, sure. Huggingface will surely be exactly like GitHub and Instagram with their extremely low and stable per-user overhead, and large, extremely dedicated user bases.
I just feel like you're saying things based on a general vibe about "AI companies" but didn't pause to look up the particular company being discussed.
Huggingface reached profitability 2 years ago. They've reportedly just started to touch the cash they raised 3 years ago. They have a tiered pricing model with metered pricing on resource heavy services. Seems pretty stable?
Your point about their user base is even weirder. They play essentially the same role for the ML community that GitHub does for software engineers, so I mean, yeah I'd pretty much expect their relationship with users to be "exactly like" GitHub's for the most part? They're where everyone has published their models for the last 6 years at least, going back to pre ChatGPT and the recent AI boom. There aren't realistically any other major model hubs, certainly not with anything near their footprint.
Basic napkin math: 5% IRR means they'd only need to 4.5x their revenue to make this roughly work. If they can finance this cheaper and/or do not have better options for their cash, it's even less.
If you assume no growth
Can someone help me out - who pays for things on HF? Are they charging the model providers?
It's not too dissimilar from GitHub, but geared towards ML. They have a 9/mo pro plan for individual users for upgraded storage/usage, and an enterprise version of Hub that larger orgs can pay for. I think the enterprise has some contract minimum + 50/mo per seat. https://huggingface.co/pro
They also have inference endpoints with metered prices, and their spaces product (though i'd imagine this is a smaller portion of revenue).
I’d be curious to see how much that’s subsidized. Maybe they’re different, but when I see ML and monthly plan in the same sentence, I see zero sustainability.
I'm curious why?
Why I don’t think it’s sustainable to run a compute-intensive business on low monthly plans? If they’re like OpenAI and Anthropic, monthly plan users can spend many times the amount of money in a month than they pay, and unlike regular lower-compute SaaS businesses, overhead increases significantly with usage. That means the more users many of these services get, the more money they lose. Some surmise OpenAI was hiding the actual cost in marketing expenses to make their business look less unprofitable. Anthropic was smart enough to focus on customers most likely to be willing to pay for API pricing, so they’re in a better position. If hugging face is primarily focused on selling monthly accounts rather than token based billing which bills more as the company’s expenses increase, its not likely to ever be sustainable without significant changes.
Most of HF's revenue comes from their enterprise customers; you essentially get direct access to their MLEs (Slack) as well as their software stack, hence the per-seat cost and annual minimum contract price. In that sense they are not particularly "compute-heavy" in terms of what they "really" sell.
Ah so it sounds like they might be closer to a regular SaaS.
This gets mentioned a lot, but the most valuable companies, by orders of magnitude, have the most profit, by orders of magnitude.
Yeah the people that say things like this aren’t looking for valuable companies, or to create value, or for sustainability — they’re looking for short-term growth.
Risk management.
Nvidia has a market cap of $5T USD today, and a decent chunk of that is due to LLM speculation.
Does Nvidia want their stock price to be at risk of being tanked by a download service being in the news? No, they want to make sure the party keeps going and is under their direct supervision, and part of that is making sure Hugging Face isn't bought by a competitor or runs out of money.
If their stock moves up more than third of percent due to this they have won... The math at these valuations get somewhat extreme. But there is some logic in it.
Interesting perspective that makes sense to me. HF is big enough to make the news
> Why would Nvidia spend $13B for what seems to be a services that gives things away for free.
To stop that! Literally. To stop those services being free.
Why would Nvidia destroy the first place we all look for models to load on our Nvidia hardware?
for 6 months?
There is a brand and that brand is really a type of call option that is very hard to price. If you are doing the valuation using the tools of Ben Graham it is not really going to work. Damodaran's the Dark Side of Valuation is the text for this.
https://huggingface.co/pricing
I don't understand who this is targeted at. You can download the models, clone the datasets free. Who is paying them and why?
This is like asking who is paying for GitHub if you can clone repositories and download code from it for free.
I guess that's a decent analogy, except the vast majority of people aren't building their own models.
They make it easy to run models. The models have to run on hardware somewhere.
This is like saying GitHub or Google just gives away everything for free
Not really. GitHub has a strong platform of paying customers and a solid product that’s hard to replicate.
Google is obvious.
Hugging Face is a file download mirror with a couple of side features dangling off.
They hit 150 million in annual recurring revenue this year.
Pretty nice dangling side features apparently.
That still leaves the company valued at 86 years of revenue
Yeah, great point. Nvidia could potentially be overpaying. Not sure how that equates to Huggingface being "a file download mirror with a couple of side features dangling off".
Absolutely none of this makes sense and the thing that amazes me is how long it has continued. Future historians will just laugh at how stupid and obvious the crash was.
Just wait until you hear that Facebook bought Instagram for $1 billion in 2012, when it was generating no revenue.
While it's probably easier to say this in retrospect, they were eliminating a direct competitor to their core business. Something so advantageous it should have been blocked by regulators.
I can't see this as being as good of a purchase, especially when it's 13x the price of what was seen as an absurdly large amount back then.
You are very good at bringing up irrelevant numbers and missing the forest for the trees
You are right, we are in a post numbers and reality economy.
Are you 15x more sure of that than you were last year?
Whether you realize it or not Hugging Face's monetization is just as obvious as GitHub's
Possibly, but they were profitable already.
You missed the part about get hacked by one of the cornerstones of the ecosystem so that you could get infinite bad press for them if you wanted.
This. They are buying a brick in the xkcd #2347 diagram
I guess we may have to start paying to download models.
Or perhaps they will start throttling downloads for free users.
I don't know what they business case is, it might be to shut them down: I suspect good free models on local hardware is a threat to Nvidia's investments in OpenAI/Anthropic.
I see the opposite — NVIDIA is aiming to commoditize the model layer and push open models that are tuned to run on NVIDIA hardware.
So much this. It's like Apple buying Shazam or any other software company, they do it to bring value to their hardware platform.
Maybe everyone will migrate to Hugging Bay for downloading models via torrent?
NVidia has been expending energy helping improve local models and inference platforms for them targeting NVidia GPUs; good free models that users can run locally rewards Nvidia’s investment in product lines for local inference (DGX, RTX PCs, etc), as well as—given their continued dominance in the space—the premium over competitors of their consumer and workstation GPUs.
File hosting isn’t that hard to replicate though. Even if they start charging people will just set up torrents for the files or lists of mirrors.
Unless I’m missing something, this feels like Nvidia having more money than they know what to do with.
Maybe they're trying to see how big the market actually is before considering shutting it down, maybe or getting lawyers and politicians to try and outlaw or restrict open models if they see a big enough opportunity.
it's literally the GitHub for AI
Github was acquired for $7B. It's hard for me to see how HF is worth almost double Github.
GitHub was acquired for 10B in 2026 dollars. And software on HF requires quite a bit more hardware expenditure to run.
AI is the current thing, HF does the current thing. Hype cycles in computing anyone?
ondemand cloud? b2b?
an FTP server delivering tarballs.
It hugs your face
This trend to vertical integration is very dangerous. We should not allow the people making tech to control the whole pipeline unless we want a permanent underclass.
Something something Apple. For what it's worth though, I agree that companies _subsuming_ others to obtain complete vertical market capture has been a very dangerous trend.
Apple isnt an analog though, in order to be a relevant analogy they would need to buy Intel, TSMC and ASML and "commit" to preserving access to other people chip manufacturing. As it is, they are guilty of reserving capacity so other producers cant access current generation tech and have to weight a cycle, which I would argue should be blocked as anticompetitive by regulators but we have a perverse definition of free markets now that defines market consolidation and monopoly as markets working instead of recognizing they are a sign that a free market has been captured and destroyed.
rant over.
The hyperscalers and OS vendors are doing. Why shouldnt hardware oems.
The open weights AI ecosystem is way too concentrated with HF. That said, it was clear they were going to either get bought or aggressively monetized at some point, Nvidia seems like it could be one of the more aligned acquirers.
I do worry about any sort of crowding out or downplaying non Nvidia-relevant quants, and about changing rules to crack down on models or datasets that for one reason or another “don’t align with their corporate values” - uncensored etc. Someone mentioned Microsoft and GitHub, they appear to me anyway to have been very hands off, I hope it’s the same model.
There are always torrents, which would seem to be a fine way to distribute models.
We also have modelscope.cn, I'm sure that one won't get acquired
It's already part of Alibaba, which has its own incentives. So does kaggle with Google. Civitai is neutral but it is mostly nsfw even though they don't show it outright. Torrenting is the Best way
I could put on a tinfoil hat and say that nvidia will have some control on the flow of the open models, so if someone like the US government want to "control" and police the models like Dario was talking about then this investment might actually make sense. The HF platform can then be used as the "controlled" channel and any other site can be designated a national security risk and blocked / taken down.
This is the world we live in now. 3-4 megacorps owning everything in every major product category - eyewear, cosmetic, consumer goods, media, tech; you name it.
We need small companies worldwide, developing the things huggingface does. The us china and Europe dominate while the rest of the world sits by idly. Torrent and seed ai models. It's not piracy
We live in now?
Has always been this way. Big companies always seek to buy fast growing startups and unfortunately the founders of these startups mostly take the money.
If you can't beat them, buy them. Hallmark of late-stage capitalism.
Potentially horrible for monopoly reasons, but if other big acquisitions in the AI era teach us anything, developers are about to get a whole lot of free and discounted trial credits.
That’s at least a plus. I will happily burn through as much VC money as they will give me to tinker with my projects.
Yes. Great for devs, for a while. Awful for overall competition and industry's health.
I think the federal antitrust regulators are asleep.
Edit: antitrust regulators' job has just begun -- we'll see how this deal gets adjudicated by the FTC (if at all).
> I think the federal antitrust regulators are asleep.
Have been for a long time. All of the big techs should have been broken up long ago.
You can torrent and seed these models via torrenting. They are not piracy so there's no problem hosting them besides maybe not having enough bandwidth
Interesting ideas, maybe the real open alternative will indeed be torrents.
... You wouldn't steal a car ... you wouldn't steal a bag ... piracy is a crime. (Girl cancels the download and walks away from the PC. Remember? :-))
That is what will happen to torrents. Followed by VPNs. China, Russia and Iran had paved the way already.
Can't you see the puzzle coming toghether?
Ai models are not piracy, because you never had to pay for them and simply seeding them and downloading them does not break their licenses
Current US government is pay to play. As in buy my cryptocurrency and you get a pardon or case dismissal, no backroom deal required. Payment directly. Blatant corruption sucks.
If the House or Senate turn that might actually stop or slow down. The market falling by 30% when the AI bubble eventually pops would also trigger it.
Except for during Biden, they've been asleep for almost 50 years.
Lina Khan @ the FTC was the best thing about the Biden administration, for me.
I think failing to take advantage of the charisma of both Lina Khan and Janet Yellen, and not making them public-facing economics gurus like Alan Greenspan or Larry Summers historically were, was a huge tactical mistake by Biden.
Fair, but the biggest mistake by far was failing to take charge of the immigration debate. The second biggest was his press secretary's insistence on announcing that everything was fine in the economy over and over as a distant second. Third was not resigning when it became clear that he couldn't really keep up with the job, or at least not trying to run for a second term. Virtually nothing else matters by comparison.
Fear over economic damage due to immigration is perhaps the last remaining unifying force among the American political right wing. Biden actually did a lot of good things as president -- arguably a lot more good than he did in his time as senator. But his administration was too eager to just run the federal government as a quiet meritocracy and avoid dealing with any of the hot political issues of the day. He and his administration fucked up so bad that now not only is most of that good undone, but we are in a dire existential situation, facing generational-scale damage that might be unfixable.
It's one thing that they genuinely fumbled the handling of the huge immigration/refugee waves spanning the entire continent and it took them well over a year to start coordinating a response (which they never really did apart from eventually just closing the border) -- it's another that they kept trying to insist everything was fine, there was no problem, there's nothing to see here. People were freaking out about it all over the country, and of course they were being heavily propagandized, but that's not the point. A strong and proactive White House would have made all the propaganda look stupid. Instead, it looked like the truth.
It's absolutely mind-boggling to look back on just how weak the president had to have been from 2020-2024, to somehow let the party of Jan 6 and the disastrous handling of the Covid-19 pandemic regain enough control of the political narrative to make Trump seem like anything other than a narcissistic mobster.
Yellen was objectively the dumbest Treasury Secretary ever. When everyone and their dog realized inflation was getting out of control, she thought it was transitory. She literally gets an F- as an economist.
And some former Roomba employees may have thoughts about Kahn.
Kahn was right about Roomba. Amazon was going to torpedo all the superior competition on the Amazon platform where almost all robot vacuums are sold in the US, plus as the e-commerce monopoly, Amazon was going to instantly have access to an army of cameras inside people’s homes to analyze personal information related to purchase preferences.
IMO allowing Roomba to hit chapter 11 was still a better option for the consumer than handing them to Amazon. They’re still in business as an independent competitor on the market, consolidation was successfully avoided.
Yellen, I don’t have much of an opinion on, but she absolutely wasn’t alone in that opinion (the nuance of that opinion being inflated by this hyperbole), and the treasury is a lot less involved than the federal reserve in doing anything about inflation, anyway.
This is a tangent to my first comment parent to this one, but also more related to the actual article at hand: whether it's Amazon buying Roomba or Nvidia buying Hugging Face, I have a somewhat radical (or is it?) opinion that large companies like Nvidia, Amazon, Apple, Microsoft, Coca-Cola, etc, should not actually be allowed to acquire companies. At all. under any circumstances, even if competition is healthy.
These companies are generally large enough that they do not need the competitive aid of buying an existing company and starting with that sort of structural advantage.
E.g., did Nvidia not have enough money in their bank to start a company to compete with Hugging Face? This is a company that reportedly has ~200-300 employees with investment rounds totaling $400 million. Nvidia made $31.9 billion in net income last quarter.
I look at a company like Xiaomi which just developed its automotive division in-house without resorting to buying car companies. I think our traditional business and finance mindset has an overreliance on acquisitions.
This is a lesser-of-two-evils situation. Before acquisitions became the new "meta" in Silicon Valley, the old meta was that gigantic quasi-monopolies, like Microsoft, burn money and man-years embracing, extending, and extinguishing your product.
I heard (literally with my ears, during a pseudo-dinner-thing, so this may be apocryphal, so you may have to do some spelunking through sources) that Microsoft "bought" the source code of some browser-project, for a percentage of the revenues that come from Internet Explorer. The catch was that IE was bundled with Windows for free, so a percentage of zero is zero.
A definite fact, is that when Netscape folded, the industry -- and the investors that got burned by the rapaciousness of Microsoft -- finally got in-sync enough to lobby and agitate for the antitrust lawsuit that almost broke Microsoft up. A consequence of that lawsuit is that quasi-monopolies like Meta, Google, etc, started buying promising startups instead of burying them.
I am not sure that a world where Nvidia just out-spends Hugging Face, via its quasi-monopoly-revenues, is better than the one we are currently in.
If I have to choose between two evils, I'd obviously choose the lesser one. But maybe we can do even better, and choose the absence of evil?
Maybe companies should have "weight-classes" the same way that most sports have those, to match opponents. (After all, despite both being remarkable sportists, Koga cannot defeat Ogawa, who is a few weight-classes heavier). Something like this is how France protects (or tries to) its own small business owners (I am told, they still have many small independent bookstores, despite competition from Amazon, and chain-bookstores before that).
The venture-capital does _somewhat_ balance the scales, but not by much, and it encourages the pursuit of _exits_ instead of _excellence_ (not shaming anyone for taking an exit, I am just saying that the alternative is systematically penalized -- only the very lucky or very protected can pursue excellence).
Roomba was not competitive in the market, no amount of Amazon market manipulation would have changed that. Best case scenario, Amazon would have invested in making it competitive. Worst case, their engineers would have been absorbed into Amazon's warehouse robotics projects.
Is either of those worse than what actually happened: the company is now a zombie brand for a Chinese company?
Of course Amazon would have changed that. You would go on Amazon and search for "robot vacuum" and Amazon would put iRobot at the top of the results. Review manipulation on the platform would be trivial.
Amazon could email/push notification/text customers asking for reviews of iRobot vacuums but then not do the same for competing vacuums, skewing their reviews higher (asking for reviews boosts ratings by gathering opinions from happy customers who usually don't bother writing a review). Competing brands potentially don't even have your contact information to ask for a review.
Go on Amazon right now and search for "usb cable." There's a giant banner at the top that recommends the Amazon Basics brand, three across horizontally, which on my desktop monitor takes up nearly 50% of the screen real estate. Then below it are the Anker cables that you're more likely to be looking for.
They would have almost certainly been manipulating pricing on them as well. For example, they could take the strategy of lowering the price of the vacuums to break even or sell as a loss leader, but use them as a data-gathering robot in your house to help Amazon sell more of everything else. They could make their Alexa smart home platform preferential to iRobot or lock out competing models.
Robot vacuums are a consumer goods category that is heavily skewed toward Amazon.com as the place of purchase compared to other retailers.
I think "zombie brand owned by a Chinese company" is actually preferable, yes. They still operate and sell vacuums competing with the other robot vacuums on the market, and they aren't in service as household data collection bots for a monopoly e-commerce platform.
I don't think the ownership of the company being foreign or domestic is very relevant to the FTC's goal of preserving positive trade conditions. Would we think the iRobot situation was a bad outcome if iRobot was purchased by a foreign company we view more positively like Miele? We only think of it negatively due to anti-Chinese bias. iRobot being Chinese-owned is almost certainly the best possible outcome for preserving the amount of competition in the market.
iRobot is now 100% owned by Shenzhen Picea Robotics of China. (https://www.sec.gov/Archives/edgar/data/1159167/000115916726...)
Yes, that's a very good company to be the owner of iRobot, because they are just a robot factory and not a near-monopoly e-commerce retailer.
They are essentially on equal footing with other robotic vacuum manufacturers. iRobot didn't go out of business or get absorbed into a larger company lowering competition in the marketplace.
It's also not the FTC's job to ensure that companies, especially ones with zero/trivial national security or domestic labor force value, remain under domestic ownership. Amazon itself is not really a "domestic" company, it's publicly traded. Anyone from any non-sanctioned country can buy shares of Amazon.
How would you define a domestic company?
> zero/trivial national security
Huh?
Robots with vision + sounds sensors and connected to the internet in professional homes across your country are definitely a security issue.
https://www.abc.net.au/news/2024-10-05/robot-vacuum-deebot-e...
One of the leaked images taken by Roomba robot vacuums shows a lady sitting on her toilet - personal.
Does that have military value? I think it's more of a personal security issue.
The company's name was iRobot, not Roomba.
I spent a little time working there around 2017. Whatever you're implying my former colleagues' thoughts on the subject are (or mine, for that matter), you're probably wrong.
I miss her. Actual government for the people.
I miss the Biden administration
Large numbers of people outside of the United States probably do.
I miss him from inside the United States too.
China and Russia are loving things right now.
I miss every administration back to Roosevelt.
That's a sad thing to have to say, but yeah.
The president who helped kil 15k children? Why do you miss him, he should be in the jail cell next to trump.
Now that you mention sleeping. I imagine one could do cool sleeping startups that clone something but exist only on paper. The sleeper startup is only launched the moment some ham fisted mega corp aquires the original and all the customers are looking for a way to abandon ship.
Won't work. Businesses need a proven track record before they can buy. With no established history of successes, this plan is already dead on arrival.
Depends who does it. If someone with the track record and budget pulls the rabbit out of the hat swiftly existing customers would at least investigate.
If you maintain a list of shortcommings or good new features it could sound like a sweet deal.
If the company was aquired to shut it down it would work even better.
Marketing is increasingly expensive. Any hype is valuable. One might as well design the product for the promotion.
True, but better nvidia than any other big tech contender. Nvidia has a very strong business incentive to make huggingface thrive, whereas pretty much everyone else has the opposite incentive.
Especially when all major labs are building their custom inference chips.
Yeah I think this is probably one of the best outcomes you could hope for if you want to use open models.
> That’s at least a plus. I will happily burn through as much VC money as they will give me to tinker with my projects.
The era of VC-funded home-delivery recipe boxes is still my favourite.
The Government plans to regulate open source ai. Nvidea is dependent on the Government to back loans, provide property, and make laws in their favor. Now they have ownership of what the Government wants to control. A perfect wedge they can use to get more from the Government.
100x this: "The Government plans to regulate open source ai." and ... s/regulate/restrict
We're entering consolidation
Yeah this is the "early netflix" era. Take advantage while you can and plan for the future.
Counter point is China can afford to keep pumping out free models for long enough to crash the AI industry, As well as spin up memory production.
Its likely in the near future we will be able to buy 128gb mac minis and run local AI for free.
Why would China want to crash the AI industry? Their goal is not to damage the United States, necessarily. Their goal is to have the best domestic AI on the planet. They intend to do that through the way that they dominate every other industry: good enough quality at a much greater scale.
Surely crashing the Ai industry (in terms of reducing commercial revenue) makes it harder for the leaders to keep raising money and so keep investing in r&d to the same levels. Thus allowing competitors without access to latest American hardware to keep up.
When did apple stop charging more for their memory upgrades then gold by the ounce costs?
They didn't, but their price increases haven't kept pace with general memory price increases (yet) so currently their pricing seems reasonable.
If we survive, that is.
That means we will torrent these ai models. They are not pirated so there's no problem doing so
Nvidia is a public company. What VC money?
I think this is good.. They have incentives to keep things free to keep people using their GPUs. I think that's one of the least enshittifying outcomes possible
This is going to suck. Open weight models need to become the norm on torrents.
Agree. this sucks already.
HF is the default platform to find models. Not just ones published by big labs but also a lot of the distilled or fine-tuned versions, etc.
If Nvidia buying HF makes it tough for all the diverse models on HF, then what are some alternatives?
It seems models are the best things to be available on a Torrent platform? Of course HF is much more than just the files but perhaps the metadata can be separate and hosted on multiple community platforms.
If HF didn’t exist, model releases would likely have been on torrents like Linux iso’s back in the day.
I'd honestly prefer that. I'm usually on 5g if not 4g and pulling models is an absolute nightmare when I basically have to use HF and even with a token getting throttled. Although I have a pretty unique use case. Pulling wads of 5gb tensor files over cellular is painful.
I am on the same boat, I live in a small Himalayan village. I have 2x5G based devices and one Wireless bridge (Ubiquiti LiteBeam M5) for a local broadband. Generally I get 50 Mbps, sometimes up to 100 Mbps
i'm traveling in an RV and can always (80% of the time) get up to 3MBps, max to 300. But with cellular it's mega spotty so pulling 3-10 5GB files then losing your connection for a few seconds/minutes completely kills that files download. I've tried about 10 different keep-alive-ing type hf downloader clients and with my 64gb ram I'm usually downloading 25-32GB models and I don't even try unless I'm in sitting in a city next to a library anymore.
It's less of a pain now that I'm not in my LLM newbie phase of trying to test out 30 different models and stick with Qwen, but I couldn't even try to download qwen 3.8 for a week or two until I got back to the city.
Starlink is the obvious option and I have it on my roof but I do everything I can to not pay that $170 a month vs my $170/quarter 5g service.
I am quite skeptical that an acquisition by Nvidia will make people move somewhere else ... The network effect remains central, if you are researcher/lab/company and you want to promote your model/dataset you go to the popular platform where most of the community is. The same way most of the public repo are still being published on GitHub despite people being pissed of by Microsoft acquisition. (I you add on top of that the cost changing your workflow, not using HF library, ... it make the transition even more difficult)
> what are some alternatives
good old torrents
There's over 3 million models on HuggingFace. So many quants. I'd imagine less than 0.5% would actually be seeded.
I don't know anyone who "finds" models on HF. The announcements always come through Reddit, HN, Xitter, and various Discords. HF is just a place where some people bought a domain name, spun up a file server, and struck it rich. If they went away tomorrow, they'd be replaced the next day.
Grim prediction:
"Quantized models are no longer permitted on the Hugging Face platform. Reduced precision models are a safety hazard and a violation of our TOS. Click here to speak with a sales representative about our many exciting cloud hosting offerings or enterprise GPU packages."
This acquisition and the Stripe acquisition of OpenRouter are puzzling. Both HF and OR, from a technological standpoint, don't appear to have much IP that cannot be easily replicated.
I wonder how much it's worth to Nvidia just to obtain a list of who's downloading which models and for what purpose. Similarly with the Stripe acquisition of OpenRouter. In the past, it would have been valuable to obtain an audience or market share or even a productive team. However, in this new age of the surveillance state ...
telemetry, orchestration, and financial
America is headed towards techno zaibatsu economy. Just a product of the dynamics of capital and power. Too much cash, Nvidia is forced to try and find ways to deploy excess capital very quickly. Most efficient way is to absorb players in emerging industries, bet on the potential for growth in new markets to help keep ROI up. It is a great day for startups, the goal is to sell out and get rich, no? INB4 China comes in and dismantles the American zaibatsus in 2245 like America did to Japan in 1945.
1. America needs to repeal citizens united, it's the source of many angles of corruption
2. I think it will happen much sooner than 2245 given how easily capital and the rich are able to move around the globe in 2026 (compared to 1945)
We simply need to bring back that 90% federal income tax bracket we had in the 1950s. If we had the same tax policy today, a CEO or investor would be limited to 5 million dollars a year in earnings. This is what fixed everything.
If a CEO cannot personally get richer by cutting wages, cutting staffing, and outsourcing; all of it stops. That was the secret of affordability. Don't let a thousand rich people own everythjng. Tax them so we can have millions of working millionaires instead of 900 non-working billionaire elites.
As those 1950s taxes and post 1929 financial regulations were cut in the following decades, the wealth inequality that led to the great depression has returned.
This is more a result of Clinton's failed CEO pay reform. It is what created this monster, not the tax bracket. Now, saying that, we DO need to tax these people higher. Eliminate all the ways they're able to squirm out from paying a fair share.
Marginal tax rates are meaningless because, even in the 1950s, the system was complex and can be gamed.
If you want to judge the net effect of tax policy over time, look at the percentage of GDP captured by federal receipts (the vast majority of which are taxes). In the U.S., it's averaged ~16.5%-~17.5% with occasional spikes and dips. Currently, it's very close to what it was in those 90%-marginal-rates 1950s.
I disagree on this. It's not the wealth that is the issue, it's the corruption that allows wealth to be converted into power. Citizens united is so backwards that it actually encodes the corruption as a right.
Citizens United is a very sound ruling.
People have a right to support candidates > they can print a sign and stand on a street corner > printing signs costs money > people have a right to spend money supporting candidates.
People have a right to assemble > they can stand on a street corner with their friends > they can hold a big sign together > they can have lots of friends and form a group and print a really big sign.
We want to encourage private business > limiting liability for owners who do not participate in the business would increase access to capital > we offer corporate forms that shield investors from liability > identity of owners may be kept confidential.
People complain about the wrong thing. The problem isn't that people are allowed to support candidates with their money, buy airtime, etc.. It's that companies have secret owners...
You said "People" a lot in your post. Corporations are not "people".
Only natural persons should be able to contribute to political candidates.
Corporations can lobby, as a corporate person, just like a union or other organization, but not contribute.
They can run ads themselves, but there needs to be a much greater wall between PACs and candidate campaigns, with the previous restrictions now null and void due to lack of enforcement.
I don't understand what you're getting at.
If it's okay for Corporations can run ads themselves, then your objection isn't to wealthy people supporting candidates or even them doing so secretly, but... only when the little guy pools donations and they happen to be pool donations via a corporation?
Corporations are just groups of people. That's the logic.
The problem isn't "corporations can do the same thing as people."
The problem is anybody (solo or as a group) can legally run an unrestricted indirect campaign.
Elon can do the same, or more, as an individual than just about any corporation. That's just as problematic as Ford or Meta buying an election.
Dark money contributions are a closely related problem that we ought to fix at the same time.
> Citizens United is a very sound ruling.
Corporations only have the powers granted to them by the state. Contributing to politics need not be one of them.
Yes and no.
No, state's cannot e.g. discriminate on the basis of race by allowing corporations only composed of certain races. States also cannot infringe on the right to assemble or speak, by prohibiting people from supporting political candidates when they are organized as such a group.
But, generally, yes. States can require that the owners / members / corporate books / etc. of a company be disclosed publicly. If owners don't want their books disclosed, then they can forego the immunity that the corporate forms provide.
> Citizens United is a very sound ruling.
> People have a right to support candidates > they can print a sign and stand on a street corner > printing signs costs money > people have a right to spend money supporting candidates.
Individuals printing signage is not where most of the funding is going though, is it?
> People have a right to assemble > they can stand on a street corner with their friends > they can hold a big sign together > they can have lots of friends and form a group and print a really big sign.
This isn't how most of the money is being spent either, is it?
I don't know how you seem to either believe the point of the right to free assembly was to give richer corporations more sway, or be completely oblivious to the fact that that is what's actually getting people angry, not the fact that citizens want to stand with signs by the street corner. Assuming you don't have a conflict of interest leading you to that conclusion, I... don't know what to tell you.
I think your objection is fairly clear in terms of 1) you point out the difference between e.g. standing with a sign vs. more expensive options, and 2) you say "right to free assembly was to give richer corporations more sway."
Fundamentally it sounds like your complaint is that wealthy people are presumably more able to be effective with their efforts than folks who, e.g. can't afford as big of a bullhorn.
Citizens United wasn't about that. There wasn't a law saying no person shall spend more than $1k/yr supporting a candidate.
This is a completely inhuman and unamerican take. Money buys secrecy, it always has. Money is a tool, exercising speech is a right. For the Supreme Court to equate them is ahistorical, plutocratic, and terrible. You sound like you support giving corporations the right to vote as well,
Where do you draw the line between money and speech? IE, would you "simply" ban all political advertising completely - one can scream from a soapbox and that's it?
Money is not speech. Money is power.
Speech is speech, and what people forget about the First Amendment is that it prevents the government censoring their speech.
People yes.
Corporations no.
What is a corporation but people? Companies are groups of people. They're one or more owners, some managers, possibly some staff. If you take away all the people, then there's nothing there.
This is ultimately about power.
Democracy is built on the idea that people are equal and have equal rights. This is only sustainable if the power differential between people isn't too large.
Corporations consist of people, yes, but the power to control where the efforts of these people are directed is concentrated on very few people, giving those people a large amount of power -- so large that without any checks on their influence on government, it undermines democracy.
It's the same argument for why super-wealthy individuals are so problematic. They're literally destroying the fabric of democracy through the power imbalance afforded by their wealth.
Assets, mind share, etc. All the things that get sold off in bankruptcy proceedings.
A railroad company also has a huge amount of steel roads with cross country right of ways. You could fire everyone, and it'd still be extremely valuable. It might even be more valuable.
Even in asset-lite software land, "Atari" the name still has a lot of value, even though none of the people are there anymore. They own the right to control the things that the neurons in millions or billions of people's brains are tied to, that their habits tie them to.
Twitter, you can fire almost everyone, make the online square less pleasant for a lot of the people, the network effects truck on. People continue to use it even as they hate using it, because most everyone else is.
A corporation is a liability and pseudonym shield.
A corporation having contribution rights multiplies the otherwise imposed contribution limits on the underlying humans.
A corporation allows tax planning opportunities not afforded to the bottom 90-ish percent of the country (such as shifting income to alternate years to avoid progressive taxation, and utilizing expenses to lower that income in ways a W2 cannot)
Corporations are granted benefits that people do not get, and CU disturbs the balance of power.
Legally, the corporation itself is similar to a person and has rights unto itself, as stupid as that sounds. Those rights are different from those the individuals who run the company have.
exactly. A corporation is as much a person as it has the genes that make a human.
> People complain about the wrong thing. The problem isn't that people are allowed to support candidates with their money, buy airtime, etc.. It's that companies have secret owners...
This was a major crux of Colbert’s “our lady of perpetual exemption” bit. People absolutely know about the shadowy machinations CU enabled. The lack of transparency is a major critique.
I wouldn't say CU enabled it. CU didn't address the secrecy of corporate forms. That wasn't at issue. CU was only about ~"Can people use money with their friends to support a candidate."
To say that repealing CU is the solution is to allow the critique to go unresolved, while arguing ~"People shouldn't be free to support political candidates."
I don't know why I've never drawn a line from our current situation to the zaibatsus, that's a great insight.
> techno zaibatsu
Reminded of this discussion from a few days ago https://news.ycombinator.com/item?id=49389372
We have the techno-feudalism and dystopia but none of the cool aesthetics from cyber punk or arguably even the real Zaibatsu. Nvidia isn’t cool, there’s no interesting aesthetics or back story, it doesn’t appear to have zaibatsu ambitions, it’s just riding a meme stock bubble.
In a different world I can imagine SpaceX to be the only thing that could come close, but well...
How dare you malign Jensen's jacket so.
Nvidia is hedging their bets against becoming too dependent on OpenAI, Anthropic, and the hyperscalers as their only customers. If on-prem deployments of open models starts taking off in corporate America, this acquisition positions them well.
Nvidia really is best positioned to benefit from the AI wave. They are the main provider for GPUs to the cloud-based LLM companies, and their GPUs are still preferred for local models as well.
So either way they win.
Unless even factoring in those advantages, they are still massively overvalued, which seems to be their fear.
> This acquisition and the Stripe acquisition of OpenRouter are puzzling. Both HF and OR, from a technological standpoint, don't appear to have much IP that cannot be easily replicated.
I was puzzled by the comments on the openrouter acquisition saying "they're just a proxy" - they're an open marketplace where models compete head-to-head, they're quite a bit more than just a proxy.
Hugging Face has essentially become github for model repositories and I think nvidia wanted to snag that before microsoft does.
That’s just two sides of the same coin.
They run a proxy for LLM providers, which inevitably creates a marketplace. They’re amazon.com for tokens.
The flip side that others are pointing out is that Amazon is sticky because there’s a sprawling, physical logistics apparatus underneath. You can’t replicate amazon.com’s business without billions of dollars and a decade of building warehouses.
I don’t see where OpenRouter has that. As far as software goes, theirs doesn’t seem particularly tricky. LiteLLM does vaguely similar things, at least for organizations where managing accounts isn’t absurd overhead.
They were first, and there’s money to be made there, but what’s stopping someone else from building LibreRouter that charges a 3% or 4% fee instead of 5%? That’s where I get dubious of their valuation.
> Hugging Face has essentially become github for model repositories and I think nvidia wanted to snag that before microsoft does.
Given that most of the weights are from Chinese labs and teams, I'm surprised China's own ModelScope hasn't leapfrogged HuggingFace.
Brand name is hard to beat. HuggingFace is the defacto leader in open models.
... and there is some of that two-sided market effect that (1) people who want to publish a model will publish on HuggingFace and (2) people who look for models will look at HuggingFace. Even if HuggingFace is poorly run in the future it will be hard to dislodge.
> from a technological standpoint, don't appear to have much IP that cannot be easily replicated.
They have network effects and strong brand recognition, both of which are hard to replicate.
Just because a huge company could replicate an OR or HF replacement, doesn't mean by any measure that users will abandon OR/HF and flock to the mega-corp equivalent. In fact even the opposite-- users might be turned off and reticent to even try the mega-corp's..
Nvidia has a market cap of $5T, and so far today the stock is up almost 10%, so that's another $500B. Paying $13B for HF is chump change to them.
NVidia have been making lots of moves recently towards supporting open weight models and local AI, and it makes sense for them to buy HF who support the same, if for no other reason than to prevent someone else like Musk buying them just to shut them down, although I assume they have plans to do a lot more than just keep HF alive.
I think a close analogy is Github. The base infrastructure is open source and replicable, and still there's a virtuous cycle that keeps people choosing it over the alternatives.
I've just about stopped trying to think about things in terms of fundamentals.
"don't appear to have much IP that cannot be easily replicated"
I'm ready to be wrong but doesn't this describe basically every tech acquisition for the last 25 years or longer?
Developing a tactile trackpad that works really well is maybe a tad more difficult than downloading and uploading stuff.
I was going to say "how about github?" ... but, maybe you're right
Github definitely extended git to a far less technical audience than basic git came from. Emailing patches or connecting to others' remote hosts to pull changes was too much complexity for many customers.
Pull requests, CI platform, authentication that is not PAM etc.
IP is easy. Tractionis hard.
OpenAI recently committed multiple felonies against HuggingFace.
Nvidia is heavily invested in OpenAI, recently guaranteeing a datacenter buildout up to $105 billion dollars.
Any reasonable criminal investigation into OpenAI's actions or negligence into this incident would hurt their reputation, their ability to raise money, and therefore Nvidia, who is invested in them.
If I was a founder of HuggingFace, I am immediately getting in contact with Elon Musk and SpaceXAI, and letting him know how that he can purchase them and sue OpenAI, this time with solid claims.
If I was particularly amoral about if I think OpenAI or Anthropic should get to AGI first, I would take this bid to Nvidia, whose entire stock price is propped up by OpenAI's over-purchasing of compute.
Not just IP. Does Hugging Face have any revenue?
First mover advantage. The first big company with the most customers stays the de-facto leader of that industry/product. Later OpenRouter and HF will start building moats to keep their customers from easily leaving. That's why everyone's still on GitHub despite it blowing chunks every week. Too painful to move.
Don't see this happening. Both Nemo and TensorRT from Nvidia are heavily invested in low precision formats and higher inference throughput as well as low memory use. It's more about what happens in relation to GGUF, MLX and non CUDA-native frameworks/formats.
Bingo.
I really, really doubt that, and I'm a bit surprised (not too surprised, HN has gotten really cynical) that this is the top comment. I think the future nvidia most doesn't want is a small number of closed labs that run away with it, and gain power to steer a large part of the hardware spending towards nvidia's competitors, as leverage in pricing negotiations for big hardware buys. Their ideal would seem to be lots of competition in the model space, driving lots of innovation in lots of areas, at low margins for the model makers, driving use and demand for hardware way up. They want the portion of the economy working on this to go up, and that's not going to happen if there's just a few companies that can afford to build models.
In that case, somebody will open a new platform to upload the quantized models and hf will lose market share
One would assume.
Just out of curiosity, how did Hugging Face have the money to run that operation?
VC funding (much of it from big tech). They have a freemium model and offer some pay for enterprise features, really just private repos, permissioning, etc. but not sure if it is meaningful
Why platform? Bitorrent is the best for all these read-only model files laying on SSDs. Agreed some tiny DHT model search engine would be nice.
Too base cynicism. I'd be willing to bet you my $200 to your $100 that doesn't happen.
The history of acquisitions mothballing the acquired assets or moving them off their original mission or letting them atrophy is too stark to support your optimism. Especially when nvidia has a direct incentive to to steer the ecosystem. For example are they going to highlight and surface alternative chip designs like grok? Or will model search mysteriously not find related models?
Nvidia doesn't exactly have Oracle's reputation when it comes to acquiring companies, but given its overall hostility towards competition and open source I can't blame people for being anxious about the news.
The most important resource for self-hosting LLMs is now under the control of a company that has very markedly kept the specialized hardware outside of the broader public's hands.
You're probably right. It was mostly hyperbole, but the older I get the more I think hyperbole does eventually come to pass in situations like this. It's gradual, though, not all at once.
Natural log cynicism and any cynicism about public corporations in our late-stage capitalism world is likely to look tame a year later. Or possibly too.
I doubt it.
I see this as NVidia placing 50% of their bets on local models as the future, which it seems may be more profitable to them than cloud (sell 100/whatever local cards, which see 40hr/week max utilization, vs one cloud card seeing 24x7 utilization).
NVidia seem like a smart company - if they want to promote this direction they are not going to cripple it by trying to limit quantized models, even though you might expect them to promote benchmarks showing the benefits of larger and less quantized ones.
It's like the smart Intel of old - support CPUs all all price points, while also promoting CPU hogging applications like OpenCV.
Ex-NVIDIA employee here who worked on inference software. When it comes to inference software and models, NVIDIA's strategy is advancing the state of the art in the open model realm. They are building software and services business for those markets that need to be competitive on their own merits, and quantization and precision tuning are techniques they use themselves constantly.
Also very silly prediction given this would dramatically lower the amount of models hosted on HuggingFace and move users elsewhere to platforms that do support quantized models (not what Nvidia wants).
The new era of thepiratebay/silk road but for LLMs will be an exciting time
In all seriousness, isn't it pretty straightforward to quantize a model locally? I can do it using mlx in one command.
That would be if Anthropic purchased Hugging Face, not Nvidia.
Nvidia literally releases quantization tools.
We really need an artifactory for GGUFs
JFrog is trying to create something like that iirc
Nvidia's LLM hyperscaler partners are actively developing custom, non-Nvidia chips.
Nvidia has a deep interest in open source models to counter the LLM hyperscalers.
Nvidia also has a big bet on robotics and local AI, which requires model efficiency.
I'd worry far more about Dario and Sam regulatory capturing the US market via a "model safety" scare.
Probably start with the abliterated ones first.
But selling more product is still on thr table until cloud AI starts the real cash drain, then therell be google like shenanigans.
Advertisment "HuggingLegs", it's hugging face for hugging face.
Jevons Paradox says no. Even more "efficient" models will increase overall GPU demand and be good for NVIDIA.
Yeah. I want to be optimistic, but this feels a lot like how there used to be multiple video hosting sites and now there's just YouTube (and its copyright filters).
Now I’m going to get a little nostalgic about Vimeo. I feel like they really tried to be a better, more civilized video platform.
Unlikely, but say goodbye to uncensored and abliterated models.
These acquisitions are not healthy. They stifle competition and make it easier for governments to censor open weight models by choking off distribution points.
Goodbye? Or maybe hello to a new platform.
Hello to the new app store and "Nvidia model approval process".
Will just help EU/ASIA to fill that gap
Sounds like there’d be space to build another company.
I am quite happy to see such a successful outcome for this team. When looking at the landscape of AI-adjacent startups, rarely do you see such a nice balance between following the hype and providing a sufficiently useful and general service that makes technology more accessible to all.
Real title: "Nvidia has been in talks to acquire Hugging Face for more than $13 billion"
NVIDIA buying HF feels like defensive move. They don't want open models become hardware agnostic. I bet we see more 'optimized for CUDA' push in one year.
Do they really need HF for that?
Dgx Spark and Strix Halo have very close specs and deliver similar performance. If nvidia makes their stack be more efficient with for example 50% more tockens on similar hardware specs agaist competitors, they don't need HF.
My take is that Chinese Labs, though slightly behind on the frontier (due to compute constraints) are on a trajectory to surpass Western labs (this is me speculating, reasons are better ecosystem creation on China's part and potentially better/more data environment). Qwen-3.5-122b was the king in it's category and noone came up with something better, even though many tried like poolside with laguna. Similar with 35b and 27b param models. I think poolside and HF acquisitions show us that nvidia really wants to have competitive models on the prosumer (~100-150b param size) and likely at the 300-500b as well. Together with a hardware to run them that's a good market to be in. And as the recently rumored Xiaomi AI cube shows us (together with gorgon/medusa halo and mac studios), this is a market segment that will have competition.
I do think it's a defensive move, but at first order it's defensive against OpenAI, Anthropic, and arguably Google. NVIDIA doesn't want to end up squeezed by those three as they increasingly make their own metal, etc.
Ensuring a healthy open-weight model market means ensuring continued demand for metal running in corporate data centers, bypassing any middleman. NVIDIA has a strong interest in a thriving "run your own agents" market.
They're actually aligned with Apple here. And in this market, Apple is a real competitor too, with Apple probably more consumer-centric, while NVIDIA probably more enterprise-centric.
That could be a factor, but the optimistic interpretation would be that they want to support the open ecosystem because it sells more chips.
Models are already largely hardware agnostic. It would be pretty hard to put that cat back in the bag.
I could imagine them building value-added services on top of HF to advantage Nvidia products (i.e. "run this model on NVIDIA cloud" with one-click), but in this moment it's hard to imagine how they could actively disadvantage models built to run on other platforms.
Nvidia's been pretty terrible for open source / free software. No need to quote Linus Torvalds here. They want to control what runs on their hardware. They want to you write code against their proprietary drivers and APIs, not directly against the hardware (which these days of course also contains plenty of software, but still).
Don't expect things to go differently this time around. Nvidia wants control over the software stack. Acquiring HF fits in perfectly. The play is long term.
NVIDIA is one of the most open labs.
They even share many of their pre-training and even post-training datasets for Nemotron on HuggingFace; for example: https://huggingface.co/datasets/nvidia/Nemotron-Post-Trainin...
Which other lab shares this?
Yes, there is no question NVIDIA wants to lock you into CUDA and their hardware. But also, they’ve consistently demonstrated the most openness when it comes to model training, datasets, and research; even before the LLM era (e.g. StyleGAN).
There’s also modelscope.cn (china’s huggingface) which is worth checking out. I would not be surprised if one day, we have to use China VPNs to download open weight models.
> NVIDIA is one of the most open labs.
Of course they are. They're commoditizing their complement.
I want to own the hardware, not play around in an nvidia fiefdom full of nvidia rules.
I'll expand on the economics somewhat. My intuition is that you can like a moat left of you in the supply chain, but dislike moats to the right of you. (I'm using left and right as I picture this horizontally drawn. It is usually called vertical integration by economists.) But free competition in your market is worst of all. Free competition right outside your moat is pretty sweet, and that's were parent is commenting on.
Nvidia probably likes that ASML is a monopolist (it's called a monopsony). The price is high and Nvidia can't scale as hard as they want to (more general: capital intensive market). This monopsony makes sure that other chip companies can't rapidly scale up and try to beat Nvidia. That there only ever was one other GPU firm (I'm prehistoric; once there were more) and they bungled it on software, is pretty sweet for Nvidia.
On the side of their customers. It would be best for Nvidia if there is free competition for the outputs generated from there GPUs. This maximizes consumer surplus and thus demand. Maximum demand for tokens, is maximal demand feeded in their monopoly. If there is a monopoly right from you, demand is curtailed, and your value is limited.
And that exactly is why you see interest from token generators for chips. Bridge that moat and gain a larger value surplus. Both NVidia and, say, China actively undercutting the token-supplier value chain is quite interesting to watch. It's like the Opium wars with us as somewhat happy customers.
In this same vein, why isn't ASML raising thousands of billions for building their own (subsidiary) chip foundries, while raising prices and starving the market (a little) for their machines.
> In this same vein, why isn't ASML raising thousands of billions for building their own (subsidiary) chip foundries, while raising prices and starving the market (a little) for their machines.
You're looking this purely through an economic lens, while in reality geopolitical factors play a huge role in what ASML can and cannot do. The US government would likely take an extremely dim view of any new external competitor popping up for their chip foundry industry (especially with all the new US plants being built or planned) and would lean heavily on their vassal/ally the Netherlands to prevent this. Unlike with China, the US has more leverage over the Netherlands[1]
The US security state and US tech giants are joined at the hip, as they have been since the beginning of Silicon Valley[1], right through the Snowden revelations through to the present day[2].
[1] https://nltimes.nl/2026/08/20/us-preparing-force-netherlands...
[2] https://www.brennancenter.org/our-work/research-reports/sect...
> > NVIDIA is one of the most open labs.
> Of course they are. They're commoditizing their complement
Then why don't they sell consumer GPUs with tons of memory. They clearly segment the market into consumer versus server/business.
There are - see the RTX Pro 6000, which has 96 GB.
There are a few problems though, primarily, a GPU with lots of VRAM and very high bandwidth is inherently very expensive (on top of which there is also the CUDA premium); AI use cases are better served by SoCs with lower (but still high) bandwidth and more RAM.
The upcoming RTX Spark [0] is aiming to fill that space -- consumer GPUs with tons of memory.
[0] - https://www.nvidia.com/en-us/products/rtx-spark/
This is not a GPU, this is a laptop SoC with CPU and integrated GPU, and knowing nvidia it will probably be even more closed than an intel CPU. You will own even less of your hardware
Nearly all ARM CPUs are "even more closed than an intel CPU" on a driver level. Nvidia stands out by supporting UEFI on ARM, which even Apple refuses: https://docs.nvidia.com/dgx/dgx-spark/uefi-settings.html
While nvidia 's drivers are closed source there's enough interest in running LLM's that you are not locked in using nvidia. Strix Halo chips have been around before dgx spark came out and deliver very similar performance.
You do own the hardware. Nvidia GPUs have FOSS driver alternatives (Nouveau, NOVA) and have supported OpenCL on the proprietary drivers since 2009.
If you don't want to use CUDA, they expose the PTX bindings to write your own CUDA alternative too: https://docs.nvidia.com/cuda/parallel-thread-execution/index...
When last looked at it, NVIDIA was not supporting OpenCL beyond 1.0.
Also, when running OpenCL, NVIDIA hardware disables multiple DMA engines, and allows only one memory transfer at a time to prevent OpenCL running as fast as CUDA.
Did NVIDIA finally allow open source drivers to access all parts and features of the card to allow feature parity? Last time I checked they were considering a plan for planning a solution to that.
People love to blame NVidia on OpenCL failure, maybe Intel and AMD should actually deliver something compute researchers want to use?
I love your insights which enlighten my blind spots most of the time, but I didn't blame NVIDIA for OpenCL's failure. I just noted a company's choices when it comes to a competing set of libraries w.r.t. to their native ones.
Having said that, I'll try compiling a OpenCL 3.0 program in the cluster, so I can report whether NVIDIA runs this software, and if yes, how well.
Yeah, however if Intel and AMD actually delivered a working 2.0 with proper support for C++ and Fortran, maybe the OpenCL 3.0 back to 1.0 reboot would not have been needed.
Likewise SYSCL although built on top of OpenCL 3.0 primitives, is mostly Intel, which also owns CodePlay, the company that delivered the first working SYSCL compute experience, again neither AMD nor Intel (until it bought CodePlay).
OpenCL up to 3.0 is ostensibly supported: https://developer.nvidia.com/blog/nvidia-is-now-opencl-3-0-c...
I don't think bits like the GSP firmware will ever be open-sourced, but the opportunity to write better OpenCL drivers has always existed. Some of Nvidia's other proprietary driver backends (eg. GBM, Vulkan) are also decently neglected, but mostly out of disuse rather than malice. I don't think any of these things mean you don't own the hardware.
I wish OpenCL was usable today like your implying...
Yeah, OpenCL fandom always blames NVidia instead of Intel and AMD for doing a shitty work.
nothing stopping you from doing that
Can't buy a decent modern Intel gpu to run AI on because of nividias "donation"
The Intel Arc Pro B60 Dual has 48GB of VRAM; and the B70 goes up to 32GB.
What is the support like for them? Can they be seriously considered as alternatives to Nvidia or AMD cards? I have been looking into buying a GPU, specifically the Radeon R9700 AI Pro but noticed the Intel cards too and was not sure what you make of them.
But Crescent Island is expected to appear soon
I stand corrected. For some reason I had written off this generation but it does look capable.
Are you joking? They just bought HF for $13bill and didn’t break a sweat. They are dominant and spreading.
Nvidia has closed drivers, which makes them light years behind AMD in trust.
Also if we were just discussing labs, Ai2 opens ~everything with dramatically less resources than Nvidia.
> NVIDIA is one of the most open labs.
Nvidia’s history with linux shows the opposite. And as a user running models on a linux/AMD stack, this information does not fill me with hope.
"lab" vs "company as a whole"
They might be right w.r.t. openness about LLM at the moment, but w.r.t. general software openness they are definitely the opposite of open.
The company as a whole bought hugginface and will set its policy, though, not the lab.
Exactly. Apologies if that wasn't clear.
_why_ have people started to call companies “labs”?!
Because making new AI models is a research activity, so the group within Nvidia (or other companies) that does that activity is called a research lab, or just "lab" for short. I don't think anyone is saying that all of Nvidia is a lab (that's just shorthand I guess).
What amuses me is that “lab” is shorthand for “laboratory” and virtually no computer research happens inside a room people would typically call a lab.
It’s a little like the trend of calling developers “engineers”. There’s no actual engineering in the traditional sense but I’m sure developers think it sounds cool to call themselves that.
If you can't tell the difference between computer science and software engineering, then at least one of those worlds contains none of your feet.
That’s not what I said and the snarky remark about my experience is unwarranted (I have more experience in “software engineering” than many on here have been alive)
My point was just that I just find it amusing that people call themselves engineers when the code they produce is so far removed from the level of rigour one would expect in literally any other engineering industry.
I say this as someone who also has family and friends who are actual engineers, if they built bridges and buildings to the same standards that many developers write code, then people would die.
This isn’t meant as a criticism of developers, by the way. Just an observation at the vast differences in the domains and thus the tolerance for errors in the process.
Likewise for labs. I’ve worked in AI startups and the science departments are not something one would think of when you say “laboratory”. I get why the term is used, but it’s still amusing.
I know language isn’t static. It’s something that evolves, like how a “computer” used to refer to a person rather than a thing, but that doesn’t stop me from being amused. But maybe the real issue here is I take myself less seriously than others so I have that capacity to be amused by the titles I’ve held?
Because they are mostly research departments (aka a lab) turned into a corp structure. It’s not a new phenomenon, just that until recently labs didn’t get $1T valuations so you see it more now
Ok, so, what research department did Nvidia grow out of?
NVIDIA has a research lab (actually, multiple given how massive they are)
Volkswagen has a couple too. Like, actual laboratories with people in white coats working in them. You don’t call Volkswagen “a lab” because of that.
Because it sounds cool/sciency.
Just like everything AI is a "model". It's actually not, but it sounds cool/sciency.
Exactly. Adam Neumann figured this out with WeWork Labs.
It sounds cool because people in our age are almost obsessed with scientistic performance.
At least AI labs are actually doing experiments.
I'm with Torvalds here, fuck you Nvidia.
> NVIDIA is one of the most open labs.
A few years ago everyone said _Open_AI is the the most open labs. How did that turn out? Lots of coy, deceiving actions till the whole company was turned into whatever rent seeking amoral borg adjacent shell of it's former past it is now.
"The proprietary shovel seller has some excellent tutorials on how to dig gold. Nobody else has such good step by step guides. Therefore them buying a shovel-agnostic tutorials and techniques method (that has a lot of info on using other shovels effectively) is justified."
> NVIDIA is one of the most open labs.
Sure, the models are open weight, but porting the code needed to run them on non-Nvidia hardware is not trivial.
Not with the help of the models!
> NVIDIA is one of the most open labs.
Dude, where's the src for GPU drivers and the firmware blobs?
Sorry, you can't say it is one of the most open labs without qualifying a proper response to the question above.
"Labs" here specifically means "AI/LLM model lab", which that part of Nvidia is unquestionably one of the most open.
Nvidia is also one of the most closed hardware developers around. Two things can be true.
Then this whole comment thread was a diversion though, as it was specifically about the hardware parts and not model training.
Well, the entire context is Nvidia acquiring HF, which is very much in the "lab" side of things, so it's in my opinion slightly blurrier than that.
But it is a good example of people talking past one another and not communicating well, I would think.
/s I thought AI can now give us the source of any binary? What happened to all the vibe coded Nvidia/CUDA drivers?
They are sharing stuff that makes you consume their stuff. Their position with big ai companies is always vulnerable (asics/direct tsmc relations)
> They are sharing stuff that makes you consume their stuff
No shit Sherlock. Name one company that shared their code to make you NOT to consume their stuff?
Well if you find that obvious (I also do) then why do you not find their motives in acquiring HF onvious or that this move would be bad for the ecosystem as a whole? Cause it's all kinda the same thing.
Their (not especially great, compared to Chinese ones) models being open weight doesn't even come close to outweigh the effect of CUDA & Co being proprietary and closed.
NVIDIA is a lot more than a “lab”.
lol “Everything you said is correct but you’re wrong because I’m thinking about something other than what you were talking about”
CUDA is proprietary for a pretty understandable reason. There's no good way for Nvidia to standardize it.
They supported OpenCL when Khronos floated the idea of a GPGPU standard to manufacturers, but OEMs didn't want to design scalable hardware or sponsor the software.
Not really just to counter Anthropic
>No need to quote Linus Torvalds here
Evidently we should, because Linus has been more positive about Nvidia in the last 2 years [0]. I've been using the open driver for years now, for both gaming and CUDA.
[0] https://binarymusings.org/posts/talks/linus-on-ai-linux-in-k...
He definitely sounds more pragmatic than before, which is, in a sense, more positive.
> This is actually one of the benefits brought by AI; it has made Nvidia a good participant in the Linux kernel space. [...] Now, when Linux is so important for AI clouds, Nvidia suddenly cares very much about Linux.
He's always been pragmatic - it's just that Nvidia's behavior has AFAICT actually changed.
He has been positive about corporations and mainstream propaganda since his CoC "retreat". He is no rebel anymore.
Now Nvidia is also premium sponsor of the Linux Foundation.
Nvidia releases some of the most open open weights models, Nemotron 3, which have the full training code open, and most but not all of the training datasets.
Nvidia is a big company. They are good about some things and bad about others.
I think they really do like open weights because they make some of the best hardware for training, and the more open weights models there are, the more people are training and fine-tuning them, mostly on Nvidia hardware.
I feel like Nvidia is one of the better choices for buying Huggingface. Not perfect, but definitely far from the worst.
The worry is not that Nvidia isn’t open about their models.
The worry is that Nvidia is trying to control the way you run those models. Trying to bake CUDA assumptions into model design, and pushing the software ecosystem to be as Nvidia first as they can.
What would be the worst three?
My pick:
1. Oracle
2. A16Z
3. GameStop
1. Oracle
2. Microsoft
3. Google
Are probably the worst of the realistic options for acquiring HuggingFace
SpaceX
> Nvidia's been pretty terrible for open source / free software.
Their strategy for AI is pretty clear and they bank on on-premises OSS models for the busines, with their really cool open-source software: https://www.youtube.com/watch?v=tmcn1-jFLWY
This is a really good watch and is a glimpse into what the actual future shapes up to be considering the current situation in where the OSS Chinese models successfully compete with proprietary US ones.
As a AMD GPU user, I feel as if trying to mandate CUDA only or some other way to increase NVIDIA lock in like that would be met with people leaving the platform or at lest simply working on the non NVIDIA formats away from hugging face. Though requiring a lot of space it's quite easy to spin up a competitor at least for hosting weights. And if they try some legal shenanigans then many countries outside the US will still be happy to host I am sure why not China?
The only thing I can see them being able to get away with is increasingly bending the hugging face python API and any other features of that sort they develop to NVIDIA only. I personally don't use that and don't see a reason to and I am not sure how many people do use the hugging face python library.
Hf’s python / transformers is a hot mess. It conflates so many different ideas into huge monoliths that it’s barely usable for anything other than the small snippets listed for trying out models.
They need to take a machete to all the cross coupling they’ve metastasized.
Totally not sure why any one would use it for anything other then if they stumbled across it and where completely green.
Arguably, this move will help AI open source market more. Nvidia has an incentive to make AI open source competitive with closed source. If OpenAI or Anthropic gains in market share, they will eventually gain power over hardware vendors as well, which Nvidia does not want.
Nvidia wants people and companies to go choose a free open model, run that model on Nvidia hardware. And because Nvidia can't fully control what hardware an AI model can run, Apple Silicon and AMD hardware users will benefit as well.
Dude, the source of an LLM is the training data and the training algorithm. Those are not open, so stop calling it open source.
Open weights correspond to "binary available" for software. Nobody would call that "open source".
(Even ignoring the licensing which "open source" normally entails.)
Many open weight models do actually have open training data and training algorithms -- I think especially some from Nvidia!
That's commendable!
Though we agree that the term isn't typically used that way in the LLM context, right?
Dude, many of them are open source and open data on Hugging face, including some Nvidia LLM models.
Hey. I worked there, and I'm no longer bound by their PR policy, so I can mention this. Also, know that the fact that I worked there doesn't make me privy to their high-level strategic decisions, this is a more look from the trenches kind of thing.
My impression I've developed in the years of working there is that Nvidia's relationship with opensource is... not intentional. They kinda suck at it because they genuinely don't know how to do it more than they want to make money out of it.
Here's an anecdotal "success story" which is also an illustration to how things might not work out well otherwise.
So, I was on the team that deals with server infrastructure. One day we get a new "feature" which was supposed to allow Slurm (the workload manager, a kind of software used to run "jobs", including eg. model training) to be deployed with distributed MySQL as a backend. The feature is all obviously written by a single developer with an enormous amount of "help" from AI. I was tasked with testing it.
Trying to figure out what it does... I realized that the "distributed" part of the feature was to be achieved by integrating with Oracle's MySQL by means of using MySQLShell (another proprietary Oracle's product). Until that point, by default, we integrated with MariaDB. Not only was it using Oracle's proprietary tool, the tool, actually, didn't support the "distributed" part of the "solution". It was pitched as the "first step on the way there".
So, I was able to push back on it, mentioning Galera, arguing that the "solution" doesn't solve the problem and will require from customers to change databases (even if they are mostly compatible... they never quite 100% compatible). And the misfeature was rolled back.
I made an effort to investigate how did we even get there, and turned out that whoever authored the "solution" had an experience of working with Oracle products, but never really tried the open-source ones. So, he didn't do a research. He just used what he knew.
Unfortunately, this is a rare win, where the evidence of disadvantages of using proprietary solution was huge and enough to turn the tide. But often it doesn't face any resistance because nobody is even aware of the problem.
If that's true, it may bode well for the future. The AI boom creates some strong incentives for Nvidia to develop an intentional strategy for software generally and FOSS specifically, and there's a chance that could influence the rest of the company in a very positive direction. Hopefully, what they learn by working with HF and having the value of their hardware products increasingly determined by their ability to run FOSS software stacks will backwash into the rest of the company, or at least make them much more aware of the problem at all levels.
I do think that they still might be a bit reticent to release fully open-source drivers, though, only because of the extent to which hardware design could be inferred from the driver source. OTOH, AI itself is making disassembling and reverse engineering binary code easier and easier, so there might not be much of a point to withholding the source in the near future.
I think this is part of an open-source play. I'm not arguing your other points, I think they're true.
They're trying to mix up the competitive landscape(that doesn't impact their bottom line, and I don't think opensource is eating their lunch), so I don't think this is fake, at least that's my initial take.
Nvidia has hardly open sourced the nvcc compiler, yet no-one here is complaining about why it is closed source.
Modular on the other hand creates the Mojo compiler gets criticised for not open sourcing it immediately and now once they do, no-one cares anymore.
Huggingface was not just a target for open source, but as a force to have open weight models run better on Nvidia against the rest.
> as a force to have open weight models run better on Nvidia against the rest.
this is the crux - if nvidia makes it so that open weights end up running better on nvidia hardware than competitor's, then it's going to prevent hardware innovation and competitiveness in the entire sector.
It's like as tho General Motors buys out oil refinery to make gas for all, but the gas somehow runs smoother in GM cars.
If you don't own the customer relationship, you don't own the profit. See App store, FB.
NVidia is delivering commodity hardware to the hyperscalers, and would eventually get commodity margins (when hyperscalers make their models work on their own hardware).
Amazing article on relevant economics of squeezing vendors - actually about antitrust ad-models but:
https://www.thediff.co/archive/ad-supported-platforms-are-a-...Perhaps not relevant to huggingface, sorry.
It's a clever move if that's what they're doing. They're restricted in China, and are likely to face stiff competition from Chinese chipmakers in the coming years. Acquiring the largest repository of trainable models and ensuring they run better on Nvidia hardware is probably one of the few moves they have for keeping ahead of the competition. I mean, it would be terrible for the consumer, but it does make me think that NVDA is a decent investment.
Why would they have to acquire hf in order to optimize their stack for those models?
Couldnt they just take those models anyway?
Well now that they own it, they can do whatever they like. They don't necessarily have to be optimizing the models for their hardware, they could just setup preferential pipelines to funnel users to their ecosystem. That seems fairly prudent given the challenges coming their way.
I assume it's because nvidia is a hardware company that produces world class hardware, and it's a compiler to target that.
Whereas mojo is a general purpose language, and we're absolutely spoiled for choice on modern languages with open source compilers.
I'm not saying it's fair or right, I still think mojo is neat, but isn't exactly comparing apples to apples.
We can stop with these weak excuses since AMD and Intel have done more for open source than Nvidia has, including their GPU drivers for Linux.
Nvidia on the other hand has not and the best they have done is a bunch of closed-source blobs which they do more closed source releases than the rest.
Mojo is open source and targets all GPU architectures for their compiler regardless of the vendor and nvcc targets their own (and both that and CUDA are closed source).
So this is directly an apples to apples comparison.
I'll give credit to Intel, they've always been open source friendly and I prefer to buy them because I'm not a gamer, so don't need the best.
AMD is another story. Their binary closed source blobs were even worse than nvidias for many years. So much so people used terrible performance open source tries just to avoid the headache. That they finally slopped together an open source version after they'd lost the GPU race isn't exactly noble. But as an open source supporter in general, I commend the effort still.
> no-one cares anymore.
possibly because it took qualcomm buying them to make that happen.
Just say you don't know.
Mojo was partially open source before Qualcomm bought them, and they were going to do open source it anyway.
Was NVCC or CUDA ever open source since the lifetime of its development?
> they were going to do open source it anyway.
uh huh.
> Was NVCC or CUDA ever open source since the lifetime of its development?
you ever ask Nvidia why? i did.
> uh huh.
Exactly. You're one of those that don't care.
Mojo's standard library was open sourced a year before the acquisition.
> you ever ask Nvidia why? i did.
The correct answer to my question is "No". CUDA or NVCC was never open sourced during its lifetime.
Since you "claim" to have asked them and know the true reason why is not open source, just say what Nvidia told you verbatim right here.
Intel and AMD have no problem open sourcing their GPU drivers for Linux, but Nvidia has a problem with that.
We can only speculate that "open sourcing" it reveals their GPU trade secrets and their intellectual property for others to copy.
I care, I just don't believe you in that statement. There were "confidential nda" notes embedded in the release that Chris didn't remove until afterwards. That doesn't scream: "we're going to open source this some day!"
If it was going to "eventually" be made open source, why not do it from the start? Why not do it a year in?
From what I was told, your speculation is incorrect. I can't say anything more than that, sorry.
I don't know why you're so aggressive in tone towards me, chill out.
I'm still rooting for Modular, though.
> No need to quote Linus Torvalds here.
100%
Disagree. When it comes to AI, mvidia has been one of the most open labs. They open source a lot things and are open to contributions
I am not sure you need to posit nefarious intent for this to be a bad deal for the industry at large. Basically the only provider of GPUs getting into vertical integration is a classic monopoly move and I hope regulators look very hard at this.
As opposed to whom else? Do you think any of the other labs or acccelerators are clamoring for open source hardware?
> They want
> They want
[citation needed]
I for one welcome our new robot overlords.
I think it's a plausible play that keeps the AI boom in session for a year or two longer.
Or at least, $13b to stay at the head of the race (or keep the race running) must be worth it to someone's desk.
There's only $50b in datacenter buildout nationally (Source: Gemini, 2026).
So it is a bit of a puzzling choice for what amounts to a pile of software, in my opinion. but I don't know shit.
Did you just quote an LLM as a citation? That's not how citations work.
"That's not how citations work." (Dude on the interwebz, 2026)
But more seriously, this is my first time seeing that as well, and I'm not sure I like it. Citing an LLM is a little like citing Wikipedia to me, you cite the primary source the LLM is quoting directly, not the secondary source.
Far worse from my perspective is that it's not a fixed citation that it's not falsifiable. It's just a mutable, generalized source, which is stochastic in nature.
It may as well say "(Socrates, probably)"
A Wikipedia link can be nice when you get several different sources provided.
So much of present day feels like being back in middle school around the turn of the millenium, with classmates (and even some teachers!) new to the internet insisting that "source: internet" or "source: google" was totally fine.
It’s the formatting and formality that bother me. Say “I looked it up with Gemini,” don’t give me some weak attempt at “proper citation” to legitimize the bare minimum effort you put in.
Why waste keystrokes when less do trick?
Because a facsimile machine isn’t a reputable source lol
Even worse is that Gemini's knowledge cutoff is still Jan '25.
2026 equivalent of “my Mama told me”
> There's only $50b in datacenter buildout nationally (Source: Gemini, 2026).
Your reference lacks authority, veracity, and reproducibility.
It came to me in a dream.
Better to site the primary source, its like googling something and then siting google as your source.
They’re buying a brand, some employees, and some momentum — not any of their software. HF probably does have propriety goodies to make it all run efficiently, but certainly not a billion dollars worth, much less 13!
We are so used to these numbers being thrown around in the AI era that something one needs a reminder that this is 13 billion, not million. Insane exit by HF.
80x its yearly revenue. Clearly they aren't buying HF for margins.
In fact, has HF ever wished to make money? They probably pay AWS more infra cost than they earn. The exit was planned all along.
Was looking for this comment, the tech world has gotten completely insane with ”valuations”. I would love to hear why it was 13 and not 5. It would still be completely insane at 5 billion, but someone though they should add another 8…
Opportunity cost for Nvidia to prevent HF from going public or being sold to someone else. It's an insight into Nvidia's market prediction and what HF told them they'd do if left alone.
No company is going to be acquired for their software alone with multi-billion valuations ever again. It should be clear by now that code alone is not where the value is anymore, if it ever was.
Yeah, the price is weird as fuck.
That huge impromptu 2023 party at the Exploratorium Hugging Face did had such amazing covid-unthawing AI spring energy, and I keep thinking about it. It was clear then they had the momentum to do a lot of things, and more so now. So I was surprised by this news.
The party is a is a relatively small concern compared to the openness and github comparisons, but since no one else mentioned it, I hope something like it happens again. Or maybe that moment has passed.
I remember when people realized gaming cards could be used for general compute (GPGPU) on certain types of parallel numeric work. It was a very cool thing for many types of hackers and science and engineering students and NVIDIA went far out of their way to ensure we could never buy it.
The optimal market strategy there (as in a lot of places) wasn't "sell as much as you can". There's often a superior strategy, when (as with HPC) you have minority industry customers who are very rich and have low price sensitivity. It's to raise the price to what those special customers are willing to pay, and to drop everyone else.
What NVIDIA did was to rip out FP64 capability, systematically, from all of their consumer cards. They firewalled off "useful for GPGPU" as a differentiating feature, segmented the market, and astronomically raised the price of what (if you were looking soley at cost-to-manufacture) could have been easily affordable to any ramen student.
(It's a more obscure version of the Intel-made-ECC-memory-disappear story).
See, e.g.
https://news.ycombinator.com/item?id=47068890 ("15 years of FP64 segmentation, and why the Blackwell Ultra breaks the pattern (nicolasdickenmann.com)")
Yes, this is ironic - it was the tinkerers using CUDA on cheap graphics cards that made Nvidia stuff useful in constrained academic environments.
True about Intel and ECC, but AMD now does similar things, even with their consumer CPUs and chipsets.
These three companies now make very sure that consumer products can never canibalize those juicy data center profits - so they make sure to limit what the consumer segment can do.
The same is true for the simultaneous NVENC video encoding session limit which is artificially locked for consumer NVIDIA GPUs (see https://github.com/keylase/nvidia-patch)
For the longest time 10-bit color was only available on their professional cards. All it took was a driver update to unlock it on their consumer cards.
I am just curious, and I genuinely want to know, how is a 150 million a year in revenue company worth 13 billion dollars?
Somewhere, there’s a slide deck that shows future revenue going hockey stick.
Curvature and convexity matters even in "hockey-stick" models =3
https://www.youtube.com/watch?v=NufJ7g63KSY
Same reason why GitHub was acquired for $7.5B at $250 million ARR which is 30x revenues:
VCs could not see any other reason to raise more money and Huggingface was not growing as fast as they thought to justify the valuation or the next fundraise.
So they might as well get Nvidia to save them from the VCs pressurizing them.
That doesn't make much sense to me. Companies don't just buy companies for absurd multiples out of the niceness of their heart.
In the case of GitHub, it was likely for data reasons + wanting to own where developers do work (VScode + Github).
In the case of HuggingFace, honestly not sure as I'm not familiar enough with their business. But I can assure you that Nvidia didn't buy them for 13 billion cause HuggingFace were desperate. When you're desperate, you sell for less not more.
> But I can assure you that Nvidia didn't buy them for 13 billion cause HuggingFace were desperate.
From Nvidia's side? You get to keep the shell game of where your money and hardware are going spinning on the table for a little longer. If the party stops, Nvidia loses a zero right off their valuation instantly.
And, as a side benefit, you get to place your thumb on the scale of the open-weight hosting ecosystem. And maybe even fund a Chinese Anthropic or OpenAI at a discount.
OpenAI just popped out an inference ASIC. Google is on their 8th generation of TPU. Graviton is out from Amazon. The hosting companies want Nvidia out of their finances. Full stop. Nvidia has to do something, or it's going to get swept away.
If they are mostly paid in NVDA stock and NVDA is also valued at 40x revenues or whatever insane multiple then it makes sense.
> Here have some of my monopoly money I can print and come join us at Nvidia!
Strategically, it matters - and nvidia’s strategy is to basically own the entire industrial supply chain of the future - they have interests in their suppliers, their competitors, their users.
In this case, Nvidia wants the easiest route from:
find model -> adapt model -> optimise model -> run model
to terminate inside the Nvidia stack. This is a boon for DGX cloud.
Now what will happen to the llama.cpp performance on non Nvidia GPUs and especially on arm64 CPU chips after this acquisition? Will Apple M* chips and cloud arm64 chips (Graviton, Cobalt, Axion) become second class?
Just now I got my hands wet with local LLMs before this was announced. Can somebody from llama.cpp/ggml.ai confirm this?
We are witnessing a set of very disrupting in the industry and it is very hard to say how things will look like. AI companies buying runtimes, frameworks, editors, model routers, model hosting providers, teams behind databases... It is hard to find anyone able to reject the insane amount of money.
Very optimistic to say this will not have profound effects on the whole industry.
> Hugging Face turned down a $500 million investment offer from Nvidia late last year that would have valued it at $7 billion, the Financial Times previously reported. Hugging Face said at the time it did not want a dominant investor that could sway decisions.
So instead they sold themselves to the same investor completely ?
Money always wins, sadly.
I mean, it's $500M versus $13B.
This isn't a good thing for open source.
Nvidia don't share CUDA, don't open source their drivers, don't support capable but older hardware (forget Pascal etc), and generally charge a premium over competitors for hardware.
This acquisition will likely solidify this general stance, reduce free compute allowance for a subscription, cap downloads, push advertising, generally favour models that are Nvidia prescribed or have been sponsored, and potentially ban models and datasets that are deemed risky legally (abliterated etc).
I see no other reason why Nvidia would want this kind of vertical.
To play devil's advocate: Hugging Face was probably not profitable, and someone has to pay the bills long-term. Nvidia benefits from Hugging Face and the operating costs are pennies to them. For them it makes sense to acquire HF just to keep it running. HF shutting down or self-destructing in the search of profits would be costlier for Nvidia than just buying it now
That said, I share all your concerns. The days of a permissive hands-off HF may be numbered
Their revenue mostly comes from enterprise deals which are very profitable, and they are in a hot industry with loads of enterprise customers paying them. Storage is also extremely profitable with very fat margins at a large scale like what HF is operating at.
They had incredible revenue growth the last few years and just broke 100M in revenue. I don't know what their internal spend was , but that was almost half of their recent round in ARR. Mostly likely they were profitable or on a clear trajectory to revenue growth. Huggingface hosts a lot of data and models, but mostly static cold storage is pretty cheap tbh.
Why do you think it ‘probably was not profitable’ it has a dominant position and there are many ways to monetise that.
CUDA is partially open and partially closed.
Closed Core: Driver, compiler (nvcc), runtime, assembler (PTX/SASS). Closed Libraries: cuDNN, cuBLAS, OptiX.
Open Libraries: CCCL (Thrust, CUB, libcudacxx), CV-CUDA (Vision), CUDA-Q (Quantum). Open Tooling: CUDA Python bindings, NVIDIA Kernel Module (Linux driver outer layer).
Nvidia is working with Red Hat to develop the NOVA driver and with Valve to develop NVK, which will be the future open-source drivers.
Nvidia supported the Pascal architecture for 10 years. No other graphics company did that. AMD recently made the RDNA 2 architecture legacy after only 5 years.
Nvidia is that most promotes open models and contributes significantly through Nemotron and various hardware-level optimizers. I think the value has more to do with the potential dominance of the open model ecosystem.
https://x.com/ctnzr/status/2072715518373777812
While nvidia may not want open source drivers, they want open weight models and this acquisition allows them to keep pushing for that.
Commoditize your complement.
Nvidia don’t fundamentally care about open weight models
They care about their high margin GPUs being the dominant platform, otherwise they would have to reduce the price of their gpu/increase vram amounts.
Nvidia are making truck loads of money and want it to continue
They actually do when all their proprietary model customers are also building their own chips.
+1 on @SillyUsername. Combined with recent acquisition of OpenRouter we see exactly what we were increasingly concerned about: tightening (chocking?) of Open Weights locally-run models. The sequence and timing of these events make the intent very clear.
Now the Open-Models crowd will try to move to some other place. But fragmentation will weaken the position. Yes, there is Civic, there are purely Chinese websites ... for those who speaks Mandarin. Which only reinforces the point.
Nvidia does frequently release new OSS Nemotron models where they implement new mechanisms.
Dummytron doesn't count.
NVIDIA is open source software first for almost everything. You cherry pick a couple of things, but it's not the general sentiment.
Assuming this deal goes through, I do wonder what this means for the future of open source models. Like it's very possible the next deepseek model host it's weight on it's site first, vs treating HF as a canonical hosting site. Just my guess, but regardless we'll have to see how labs (and even countries) respond to a less neutral HF.
Is it time we have torrented version of models available for download ?
Are there any HF alternatives besides https://modelscope.cn/, particularly any based not in China?
someone mentioned torrents as an option.
Marginally misleading title, article mentioned that "Nvidia has been in talks", not agreed to anything just yet.
https://www.theinformation.com/articles/nvidia-agrees-buy-op... is a little more definitive but paywalled and still doesn't confirm the other side of the deal - Hugging Face agreeing to the purchase.
The companies have aligned incentives so I don't think this is a terrible acquisition for customers.
Vertically integrated monopolies naturally have aligned in incentives for themselves, which allows more capture which turns out bad for customers. Whether it is a monopoly is an open question.
This isn't vertical integration. This is a commoditize your complements play and that does benefit customers. Nvidia benefits from supporting the open model ecosystem, if models are a commodity the gpus become what's scarce.
Someone with financial / decision making weight their is going to ask why they are commoditizing models that run on "others" GPUs .... Since doing that makes their gpus less of the scarce resource..
Oh, I totally agree, this alone is not vertical integration, but can be a path too it, long term being able to vertically integrate undercutting others that would be on top of the chain then retracting the open model.
>Vertically integrated monopolies naturally have aligned in incentives for themselves, which allows more capture which turns out bad for customers.
Apple's devices have resulted in a great increase in quality of life for myself and family members who used to waste a lot of time with Windows drivers/BSODs/random updates/malware/etc.
It's been almost 20 years, and it's turned out OK.
of course it is
works fine for now
whats nvidia gonna do except make it worse?
usually buyouts go something like this:
1 buy company
2 fire various people
3 enshittify
hugging face even said they didnt want to accept a 500 million dollar investment from nvidia, because they didnt want nvidia to run the ship.
instead they sell it... guess who'll run the ship?
https://techcrunch.com/2026/08/24/hugging-face-reportedly-in...
What an absolute bag get for the hugging face team. Way to get out on top.
Will someone back up important models to an Anna's Archive style website? Or will there be torrent trackers?
I really hope they retain and pay Georgi Gerganov. We are toast without ggml.
Heh, thats a weird way to announced the death of HuggingFace.
It feels really weird to see this when I keep seeing the CEO and CTO of HuggingFace push for local inference to win.
Why? If anything it makes complete sense:
1) Local inference means more general GPUs and less ASIC hardware. Only big companies can push ASIC because of the software required, meanwhile nVidia owns cuda which is the standard.
2) Local is less resource-efficient per chip (chips remaining idle much more, meaning more chips required).
3) End-customers have less bargaining power compared to hyper-scalers. Although this might change if customer hardware start behaving more like phones (SoC with everything packed in), but even then the SoC makers will likely still have less bargaining power than hyper-scalers. But then nVidia could potentially make the whole SoC too.
So overall local-inference users = higher profit margins for nvidia. They much rather have every business on the globe buy one nvidia rack (or every laptop have a beefy GPU) than have 5-10 hyperscalers buy a few hundred thousand.
The hyperscalers were stable customers buying far more expensive equipment and NVidia has also made a bank selling a lot of auxillary hardware like Mellanox to AI datacenters.
But the spending spree is probably coming to an end with the looming IPO's and NVidia is probably trying to hedge their bets by making themselves the sure bet once big-AI stops monopolizing RAM and everyone races to get their local setups.
Nvidia is also pushing for local inference IMHO. They want open models and competition in the model layer, not two big labs controlling all of it.
You forget that Nvidia has also been the top consumer GPU player for 20 years.
AI companies seeking to release their own chips and Apple Metal and other unified memory solutions will all eat into Nvidias high margin GPU sales.
This can only be bad news, Nvidia didn’t buy hugging face to be good custodians but for business reasons.
Let’s hope an alternative platform emerges and takes off.
Pets.com, here we go!
Just a little bit longer and this whole "AI" insanity might finally be over! :)
I'm puzzled by the reactions. This is not a good thing. Yes, they're releasing more open source code and models, but they do it BECAUSE OF pressure from the community and other open source projects.
But Nvidia is a terrible open source and consumer company. They gatekeep a lot and oftentimes it's only open source in name. Outside contributions are often slow-walked or rejected if they don't align with business incentives , and leadership is retained 100% in a couple of people from a certain country.
Linus Torvalds: 'Nvidia has been the single worst company we've ever dealt with'
His other comments on Nvidia often contain expletives.
Linus isn't wrong but at the same time NV has shipped more compute than AMD and Intel combined to consumers. The kind of performance I get out of a modest outlay never ceases to amaze me.
Sales volume has no correlation with how good a company is for an ecosystem. See Microsoft, Adobe, Apple, Sony, and so on.
NV is a very different beast from all of those. I have yet to regret buying any of their products and I wouldn't touch your list with a stolen 10' pole.
In fairness, most of those comments were made before Nvidia capitulated in the EGLStream war and released open kernel modules.
Isn't it super easy for the community to just replace HuggingFace? Isn't it pretty much just a repo/index for open-weight models? Why is it even worth anything?
> Isn't it pretty much just a repo/index for open-weight models?
No, its not just a repo/index (they also have training, inference hosting, and they develop/maintain a bunch of core AI infrastructure software), and even if it was just a repo/index, replacing a bug centralized repo/index that used by an large community isn’t trivial.
Not just a repo/index but they also offer reasonably-priced compute, with a free tier not to sniff at, on which to run the models.
Network effects. It's like a social network for LLM nerds as well as hosting and rating models, etc.
It also means that finding models that aren't "approved" will be dealt by other websites.
good or bad, it comes down to a financial decision. Nvidia was willing to offer the highest bidding price, and HF was willing to sell.
Anyone could comment or speculate what this enormous valuation stems from? Sources list their revenue as $150M? If true this is likely one of the biggest valuation gap I've ever seen. IMO hugging face is not something could not be reproduced, perhaps not very easily but I see its business model akin to github's. Various github alternatives exist and so will hugging face alternatives.
Huggingface is not a product, it's a community. It's the go-to place where everyone who has anything to do with open AI models gathers. You could trivially reproduce their stack, but building such a huge AI community around a single place is probably impossible by now.
I don't understand the CUDA lockin in 2026...
Surely anyone can take any piece of CUDA code and tell some LLM to port it to another platform and keep grinding till performance is identical?
Sounds like that's what z.ai did to get GLM-5.3-Flash running on Huawei chips.
My prediction is that HuggingFace will take up the challenge with OpenRouter (now Stripe) and ollama.com (Facebook)
It could go either way. I think its better for Nvidia to play both open sides and closed models as their chips will be used in both. The only thing that compromises them is that there is a lot of investment they have in the closed models.
Time to see how Jensen plays it.
Good ol commoditize your compliment model. Sell GPUs? Make LLMs cheap.
If Anthropic and OpenAI makes their own inference hardware, this is a shot across the bow for making their business worthless.
Expect the next NEMOTRON to top the AI performance indices.
Out of all the companies that could have acquired hugging face, I think nvidia is the best fit. If it had to happen, happy it was them
I hope they're good stewards. This reminds me of the Microsoft GitHub acquisition in terms of the importance to the broader community.
As someone who've played video games and obsessed over graphics cards long before this all started, don't get your hopes up.
as gamers, we got burnt by nvidia way too many times. I'm still holding grudge over shutting down 3dfx.
3dfx had their own API which locked in game developers. This was far worse than anything NVidia has tried
have you heard of PhysX, Hairworks, or the CUDA moat?
3dfx hardware didn’t run anything but Glide very well. It did run some OpenGL after iD twisted their arm, but it was a really crummy implementation
While ATI and Nvidia never tried to implement a Glide emulation layer, several hobbyists did and 3dfx shut them down with legal threats
Were there any legal barriers to ATI/AMD or Intel implementing CUDA or PhysX on their systems?
Nvidia is indeed a terrible company when it comes to open source, etc. however, as someone who has been gaming on desktop hardware since the 6xxx card days, Nvidia hardware has always worked. I switched to Linux full time since the 2XX days (maybe it was the 280 gtx?) and never had a lot of the problems everyone else got on Linux (using only the closed source drivers).
Likewise, their hardware has been rock solid and very performant for me. I bought most of my current setup second hand and they've been going strong for years now.
NVIDIA introduced programs like The Way It's Meant to be Played, optimizing major game titles specifically for NVIDIA architecture, which made competitions like AMD cards underperform in critical releases.
I'm old enough to remember.
I fail to see how this is a problem?
AMD could’ve done the same.
Amd and Intel have the same programs.
But they don't/didn't have the same level of market share as Nvidia, particularly in the PC gaming market. Nvidia had 65%-85% market share, and still worked with game studios to make sure their competitions failed. That's the opposite of good stewardship that's all I'm saying.
You are being disingenuous.
They worked with studios to optimize games for their hardware. I don’t think they went around sabotaging other companies hardware. They did what was good for them.
Why did competition not do the same?
3dfx was going through bankruptcy
You Jews just make shit up lol
No gamer had a problem with nvidia.
Many bought their mobos and video cards.
Mac was pretty hated, Steam was very hated, we didn’t bow to any software company.
Nvidia actually made hardware.
Your propaganda is so awful because it’s always obvious you have no experience
I think they will be, Nvidia has released open source model that also included the data it was trained on. I think they are the only ones that have done that.
Handing out digging spots if you are the shovel manufacturer sounds reasonable.
As long as the spots continue to be compatible with shovels from other shovel manufacturers
Fix your title it's not finalized yet!
According to The Information, it seem it's finalized? https://www.theinformation.com/articles/nvidia-agrees-buy-op...
Then use that as the link.
Everything I can find online is referring to this one source. That doesn't tell me if it's happening or not.
Waht is Hugging Face's protective moat?
Why can't everyone on it just move elesehwere?
Guess the answer is scale, same reason folks don't leave twitter/x.
| Nvidia agrees to acquire Hugging Face for $13B
The title is not the linked article’s title. It is the title of the first article in the description.
FWIW, “agrees” is a weird verb. Kinda sounds like they are doing this out of kindness and not their own interests.
Remember when Facebook bought Instagram for a BILLION dollars and everyone thought it was insane?
THIRTEEN BILLIONS for ONE THING.
When Facebook bought Instagram they basically bought a photo sharing app with 10-50 Million monthly active users. Today it has 3 Billion monthly active users. In hindsight, $1B looks a very good deal for a giant like Instagram. But it wasn't a giant back then, it was just a photo sharing app and it was really insane. So it must not be about the app or the network. Facebook paid that price to enter the mobile social media market as the market leader.
BTW Instagram raised $50 million at the valuation of $500M, just 4 days before the Facebook acquisition. %100 return of investment in 4 days, I think that's insane.
I think everyone just reads *illion and thinks 'lots of money'.
The amounts are incomprehensible at this point. I don't think anyone can conceive of 13 billion dollars accurately, including the people brokering this deal, they're just thinking of bargaining chips and weighing them in comparison to how many they have.
Fun fact: a billion is 10 to 12th power in French and 10 to the power of 9 in English.
A US billion is 1 000 000 000, a French billion is 1 000 000 000 000.
(French as in francophone, not exclusively from France)
Also consider:
Nvidia is investing $1 billion in Poolside and paying $6 billion to license its technology and hire most of its engineers.
They are the elephant in the room, with their CDS sky-high. Sounds like they are opinionated on the whole AI thing, trying to drive this with open-source models, countering OpenAI using Jalapeno.
Looks zero-sum for the players.
All the while Google silently planning to get milk from all layers.
I can’t imagine any way NVIDIA could make this worth its money that doesn’t suck for everyone else
Nvidia buying Hugging Face would give them even more control over the AI ecosystem. The big question is whether Hugging Face could remain truly neutral once it’s owned by a chipmaker with plenty of competitors.
No Hugging Face as you know is dead it’s just a matter of time.
Who is hosting the next great model hosting platform or community?
Thoughts on WebTorrent?
What should we do?
stripe buys openrouter. nvidia buys hugging face. everyone on the hunt for the app that will function as hub/broker/search/marketplace for models.
They were already pretty vocal about it, but this makes Nvidia pretty much the de facto face of open weight models.
As battle lines get drawn over duopoly vs. open weight it’ll be interesting to see what Nvidia does. They definitely want a piece of more of the stack especially as Huawei chips become more and more of an alternative to cuda.
Alibaba already has modelscope and their own chips, and qwen models. Nvidia is doing the same with chips, huggingface and nemotron models
Started from an ugly repository and ended up making history in less than 10 years, from `pytorch-pretrained-bert` to huggingface, well deserved, its fascinating to follow.
HuggingFace offers abliterated/uncensored models, which would seem to run contrary to the "AI is too powerful for regular people" narrative that the big players are pushing.
My primary concern is that Nvidia will bow to the pressure and restrict abliterated/uncensored models on HF.
Yes, this is a real possibility imho.
Having Nvidia behind HF will now probably have a bunch of litigious entities salivating to sue them for not only allowing, but also distributing uncensored AI models that will then be used for deepfakes, porn, spam, scam, hacking, etc.
Sure that could have also been done to HF before, but I'm thinking Nvidia is a much juicier target.
Should also now be much easier for the government to just eventually force NVidia to restrict access to Chinese open models seeing as it will now become an American company that needs to obey to American law and we all know how American AI companies are lobbying for exactly that.
>Should also now be much easier for the government to just eventually force NVidia to restrict access to Chinese open models seeing as it will now become an American company that needs to obey to American law and we all know how American AI companies are lobbying for exactly that.
Using regulation to avoid having to be competitive is the American Way!
In all seriousness though, probably time to start an underground equivalent to HF.
Maybe we'll eventually have some sort of Anna's archive for AI ¯\_(ツ)_/¯
Pretty sure Nvidias dream is that OpenAI and Anthropic get into a hacking war using Nvidia cards.
The problem for them is that the leading provider of training and inference is actually AWS...
That is a very good point. I will set aside some storage and download those models that I think are most at risk from a corporate clean-up action.
I don't think nvda has ever pushed the idea that ai is too powerful for regular people.
That's the anthropics and openais of the world.
OP said they will bow to pressure, which just means that governments will be able to control nv and get them to ban the obliterated models, implement ’safety’ controls on all uploaded models.
Very clever - they bought the distribution platform for AI!
Nvidia’s backstop deals are now reaching $130 billion. If neocould sales collapse Nvidia can direct that capacity towards Hugging Face, and recover some of that by selling directly.
I identify as Hugging Face...
Pretty good for a little github-ish clone.
The Microsoft GitHub comparison is the right frame. Worked out fine there, hope the same here.
This whole thing made the AI attack on HF even more suspicious...
Like some other folks, I wonder whether this will be a good thing, or a bad thing.
I feel like if Nvidia ends up turning into a bad actor, in terms of restricting/censoring models... another HF will spring up.
What does Linus’s hatred of NVidia drivers imply for this situation?
The other hater is Apple, Linus’s isn’t alone…
What will the long term effects of this be? Models on Hugging Face that only runs properly on NVIDIA hardware?
Gatekeeping, censorship. Locked in vendor ship. lot's of things ending in "ship" and "ing".
Nvidia for Hugging Face will be even worse than Microsoft for GitHub and we know now how low the bar is here.
I heavily disagree.
Nvidia has a strong interest in open source AI being a strong contender to proprietary models. They don't want a single AI company to win, as that company would then have enormous leverage over Nvidia, and could perhaps even erode the Cuda moat with their own chip spending.
They want the AI market to be hypercompetitive, with AI companies focusing on competing amongst themselves instead of with Nvidia on one side, and many self-hosters / small inference providers buying Nvidia GPUs for large open models on the other.
It's in Nvidia's business interest to be a good steward of Huggingface, while being a good steward of Github is at best incidental to the interests of Microsoft.
NVidia has a strong interest in profit. The only reason we are allowed to live in chip shangri-la is because they can make a profit out of it, nothing else.
Nothing you wrote contradicts the post you are replying to.
I agree with you
> Nvidia has a strong interest in open source
Linus would heavily disagree!
He said 2 years ago they are okay nowadays (they were not in the past).
source: https://diginomica.com/kubecon-china-33-and-third-linux-long...
But he also says why, so he knows as soon as Linux isn't useful for Nvidias revenue anymore they will be gone
All the big boy AI stuff runs on servers, which certainly aren't going to be running on Windows or Mac anytime soon. Linux _is_ what all this NVIDIA hardware is going to run on until... what exactly? FreeBSD overtakes Linux in the server space?
Who knows what i sthe next big thing after AI. Maybe something that doesn't need Linux?
And I'm not so sure that Mac is out of the equation
> Who knows what i sthe next big thing after AI. Maybe something that doesn't need Linux?
And Nvidia hardware was running on Linux before AI as well...
> And I'm not so sure that Mac is out of the equation
Mac servers exist but anyone serious about running at scale isn't using them for a number of reasons, not least of which is that Apple simply doesn't make real servers anymore...
> Apple simply doesn't make real servers anymore...
That could change.
Who says they don’t switch to hardware manufacturing for AI servers
They have the money they have the capability design and engineering in house and they are vertical. The question is whether or not they have the will, one thing that might help them come to a decision is that they now have an engineer CEO from the Apple Silicon, part of the company and not a bean counter.
Can we at least let the early days of AI play out before we try to guess then next big thing? ChatGPT isn't even half a decade old.
The half-life is becoming shorter partially due to AI
Disingenuous quote. Missing the full “open source AI” phrasing.
Yes, this strategy is known as "commoditize your complement"
As long as the models run best on Nvidia hardware. What will happen if models are faster on Apple or AMD hardware?
HF CEO keeps posting about how great local models are running in his Mac, it would be funny to see if he replaces his MacBook with a 500W Nvidia laptop after the deal gets through.
But more importantly for business, if HF fails to use the upcoming ASIC inference chips for their ZeroGPU after the acquisition, their competitors using them might have an advantage.
Nvidia being making it clear that other hardware models will permanently not become second class citizens in any way would be a great start.
For the last few months, I’ve been working on a vendor-agnostic inference library. Have 3 backends so far: legacy D3D11 for compatibility, D3D12, and Vulkan 1.3. I have reasons to believe nVidia deliberately crippling Vulkan API for their consumer GPUs. Couple examples to be specific.
nVidia driver sets quite low number for VkPhysicalDeviceLimits::maxTexelBufferElements. I don’t think that’s a hardware limit because I have D3D12 backend doing the same thing on the same hardware.
Vulkan performance is not great on nVidia. On all AMD cards I am testing, Vulkan 1.3 is the fastest backend. On nVidia however, D3D12 is faster despite tensor cores (WMMA / wave matrix multiply accumulate / cooperative matrices) are only available through Vulkan, D3D12 is using shader cores exclusively.
How could they control other hardware models?
This is just one company. If other hardware is better and they don’t provide access to it, won’t people just leave HF??
Is this somehow more of a monopoly than I am imagining?
Yes, they could just say they're taking it towards prioritizing models that only run on one kind of equipment and making it harder to find, support or list models that run on different hardware.
The acquisition sets up corporate interests to be able to increasingly drive it.
I hope better for Nvidia and hopefully it can be cleared up, and maintained.
Exactly. Just tweaking the order of suggested models for a search query could already have a huge impact on model popularity.
Talk is cheap, so no need to claim that in the first place. Of course they could make it legally binding but they won't do it.
They will be as free as the Washington Post after the aquisition by Bezos.
Wait and see is the only thing we can do.
You haven’t been paying attention to Washington Post isn’t free to do anything they want under Jeff Bezos…
Prediction Apple will find the exit…
Open AI's jalapeño would be an example of this exactly...
But Nvidia isn't the only gpu maker..,
MS also have interest. The problem is that microsoft is fucking incompetent at running it. Not sure if NVIDIA is any better on that front
If you wanna sell pickaxes to miners, you want a lot of independent miners doing well.
HN failing to understand embrace extend extinguish yet again I see.
EEE is impossible already. They can't close pandoras box now.
Why is it alarming for a shovel salesman to also sell plants?
Context: Liz Lemon has been buying two products together because one of them creates a need for the other.
https://www.youtube.com/watch?v=ZZ7oht6TD9cThat's not vertical integration though. Vertical integration would be the corn chip maker buying corn farms for example. I don't think there's a name for "buying makers of complementary goods".
It's called a private equity. :-)
vertical integration
"In microeconomics, management and international political economy, vertical integration, also referred to as vertical consolidation, is an arrangement in which the supply chain of a company is integrated and owned by that company." [emphasis mine]
https://en.wikipedia.org/wiki/Vertical_integration
horizontal integration
"Horizontal integration is the process of a company increasing production of goods or services at the same level of the value chain, in the same industry. A company may do this via internal expansion or through mergers and acquisition" [emphasis mine]
https://en.wikipedia.org/wiki/Horizontal_integration
Anything else you care to throw at the wall to see if it sticks, just go ahead and assume I disagree with you given how our interaction has gone so far.
diagonal integration
The sinister nature of that integration doesn't make this one sinister at all.
Open source models are only there so the closed ones wouldn't be attacked from every angle.
To be fair Microsoft haven’t done as much integration with their eco system; such as integrating it with Azure DevOps as they could. And long may it continue.
You missed the whole game-ification, enshitification, copilot-ification of github, and open source theft for their AI training episodes
Always like that with Microsoft apologists
Not a fan of defending GitHub, but TBH them launching GithubActions made me abandon all other CI platforms I was using in the past, I even left GitLab just for that.
What sold you on GitHub Actions? The one 9 of reliability?
https://www.githubstatus.com/
Not sure what you’re intending to show.
That page shows 99.5%+ uptime across all 11 of the services provided.
To do that at a small company world cost significant money.
To have it integrated and cheap for all those small shops is very valuable to them.
It shows 98.3% for actions for me
https://ibb.co/PsMkpJFY
99.5% uptime is nothing significant...
Yeah but it's sufficient for the largest part of CI needs. Most people are making CRUD apps, 6 9s reliability is not required there.
not really, I've ran into Github Action downtime and you can't run tests or anything so either you wait or you just let stuff merge
and again don't know how this is acceptable in 2026, for a paid CI service
and I'm not talking about 6 9s, I mean, 99.5% is terrible
I never said I paid, I was referring to my opensource repos.
A 99.5 means over one year you will need to wait about 40 hours total for the issue to be solved. What kind of high pressure crud app are you making where this is a problem?
we have technology, 99.5% is embarrassing for a company like Microsoft
it's 2026, not 2016
and that 40 hr may be that over 40 days you just have to randomly stop working if you depend on GHA for something
and why are other services not struggling like this?
Github hasn't changed that much overall.
The copilot service and the training on open source would be the same if Microsoft hadn't bought GitHub, it would just be branded differently.
Have you seen github outages?
Well a lot of the outages are copilot which doesn't change my argument that already holds copilot separate.
Oh yes I can totally believe they use public and private repos for their model training. It is surprising they aren’t ahead of the curve for AI coding like Claude code, codex or cursor because of this.
I very much doubt that. Imagine the PR nightmare and potential liability if someone managed to extract from the model credentials in a private repository.
Explain to me how using OPEN source for training is theft? I've (admittedly skimmed) quite a few licenses, but I really dont remember anyone restricting reading/indexing source code?
MIT license includes: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
The argument is that AI models trained on open source should include the copyright info for all projects blended into the weights. And since they don’t, it violates the terms of the license.
You don't relinquish copyright by using a FOSS license though, right?
I'd trust a hardware player to be way more focused on reliability...
What hardware player other than Apple would you give that same trust to?
What happened to GitHub?
https://mrshu.github.io/github-statuses/
That looks roughly like a service being hammered by AI agents starting 2025, with no discernible connection to a 2012 acquisition by anyone.
It was 2018. As someone who worked at GitHub during the Microsoft era, I think Microsoft was a pretty reasonable steward of GitHub right up until Copilot started getting popular. After that, leadership stopped investing in the core product and infrastructure and either incentivized people moving into the Copilot org or just fully reorged teams into it regardless.
The load increase from AI is definitely significant, but I think with proper investment they would not be having this many issues.
This is the opening move of the end game for the current "AI" wave.
Hyperscalers and hardware manufacturers will absorb the overgrowth and hopefully (for them, sucks for us) settle at the top of the software value chain. The only way to make all the money poured into compute for the last 4 years pay for itself at any level is selling people and corporations on very inefficient software for the next couple of decades.
Not too different from what "the cloud" did to this market from 2015 or so...
So anytime someone comes out with something efficient it will get bought and bloated?
Businesses trust brand names, not efficiency.
In America, yes
Can you think of examples of that not happening?
I mean, haven't you just described VC?
And SV in general. Thinking of Skype and Slack as prime examples on top of my head.
> Not too different from what "the cloud" did to this market from 2015 or so...
I mean for all the inefficiencies of the cloud, it solved a lot of problems. It also created a new category of problems but rarely does any particular technology arrive as a pure boon without it's own compromises. Despite it's issues and despite how hot ASS some implementations are (looking at you Azure) I think cloud infrastructure you can at least say does solve a lot of problems for a lot of firms. I can't remotely say the same for AI.
It has a lot of uses don't get me wrong, but not nearly the number being pitched currently, and I don't know that I've seen any that I truly can't live without. And at the prices that are going to need to be charged when we turn the proverbial profit lever... I mean I'm sure tons of huge software houses where shipping is all that matters, behind things like quality, maintainability, the sanity of the development team, what have you, AI code assistants will have a lot of uses and the company will (probably) pay for it. But I think it's a stretch to say it's even remotely as good a trade as Cloud infra was.
In the handful of years since we've gotten all these supposedly revolutionary tools, software quality has already taken a gut-punch, will no sign of that slowing down, quite the opposite. And that's not even going into all the AI features being crammed into everything that few, if any users want or use. In fact the obsession with shoving AI shit into Photoshop instead of fixing any of the issues that've been present in that software since ~2009 was the straw that broke the camel's back for me and I've left Adobe behind entirely, and I know for certain based on communities I'm in, I'm far from alone in that.
The purpose of the system is what it does.
The goal is to increase return on capital.
Take a look at the historical developments of wage participation in global income, labor productivity growth vs wage growth, and so forth. It works very well. As long as the most capable laborers are paid well enough to go along, the rest of us have little choice. Especially after citizens united basically privatized American elections.
The inflection point is whether or not everyone else can convince the "most capable laborers" who are about to be cut from the "Most Capable Laborer Club" to join the Tang Ping Rebellion before real price discovery happens on their salaries.
No one seems to get that you have to do a general strike BEFORE they lay everyone off. It's a gambit. But either you actually were all that valuable and you can get your job back if it fails, or you weren't and you finally acted in your own self interest.
So where’s the return? Outside of annualized numbers I haven’t even heard people pretend that OAI or Anthropic are profitable. If this is all about ROI there’s sure been a lot of I for as yet unrealized R.
Have you seen the numbers for public companies?
We can't discuss the finance of private companies so we have to wait for their IPO, acquisition by some public company, or bankruptcy to find out more.
The story written in the public numbers, from corporations or government statistics, is one of rise in factor productivity, rise in capital returns, and decline in wage participation in overall income.
I'm merely observing that it seems to be the latest chapter in the development of the capitalistic corporation.
IMO the top end goal is to allow capital to access skill without allowing skill to access capital. IF they can make these products work as advertised (big if, very very big if) the corpos can fire shitloads of low-end workers and give their middle managers access to these AI models and nothing else really has to change.
Workers lose their ability to earn a living, but OpenAI and Anthropic become the gatekeepers to effectively all productivity.
I know I sound tinfoil hat here but I don't see how else the numbers work. The only thing full-priced, profit-earning AI can possibly be cheaper than is, in my mind: as much of the workforce's salaries and cost of benefits as it can manage to offset, put together.
It's a great plan if you're a CEO who can't see beyond the next quarter's earnings call. Less so if you want things like, just pulling from a hat here, a functioning economy, a stable society, the ability for humans at large to live. But it's not like the owning class hasn't been undermining all of that for the better part of 50 years anyway.
Who (what) would all these middle managers manage? Agents? Why? If agents were so capable, they'd sure be capable of managing themselves or each other...
I mean I did word that carefully, "as much of the workforce as possible." So yes entirely possible that the middle managers get automated out too.
I genuinely don't get what the endgame here is, just AI's talking to AI's everywhere and somehow they think everything just keeps on making money I guess? But then again our current crop of oligarchs are pretty mediocre all around, so calling any of this a "plan" at all feels a stretch. Just cut costs every quarter, make the products worse, fire everyone who knows anything and sail off into the sunset making more money than any human being can actually spend in the process.
And VC capital is now buying democracy...
Someone gets it. The start of the end to the AI bubble bursting.
No, see, I'm making the opposite argument. This is not a bubble, this is a deliberate play by capital owners to increase returns on capital to the detriment of labor. Much like "the cloud" before. The increased capital intensity in software was inevitable and it has accelerated since 2022.
Which is the start of the bubble bursting.
VCs invest, no one can compete and those with the moats survive.
Why? Aren’t private markets willing to invest in AI companies? Was something wrong with their arr? What?
I made a joke to my teammates today: "This will half the amount of AI startup in Europe ..."
wonder if the article got updated? Currently it reads:
>The companies have not yet reached a deal, and the talks could still fall apart, the person said. Business Insider on Sunday was the first to report that Hugging Face was fielding takeover interest.
Will the FTC block this one? Probably not..for money reasons.
Me, discovering only now that Hugging Face was founded by French people.
We're definitely better at maths than at promotion.
The lowest hanging fruit that hf could offer is community monitored commands for running local models.
Right now it is a pain to find the correct incantation.
Monumental implications on OS models. Proper investment in US OS incoming? HF has the best possible distribution to that audience
There goes the neighbourhood.
NVIDIA had more open-source models on huggingface than any other company. A lot better them than any other frontier lab, tbh.
Hope the first thing Nvidia does is change the name and logo
Hold on, these say no deal has been reached yet.
Huggingface sold out. Sad day. All the good companies lose their 'dont do evil' clause as soon as they make bank
You've sold out when you became VC Funded... It's just a matter of how long the free punch lasts.
What, are you expecting them to just work for good vibes?
To be fair, this is the best thing that can happen for the founders. I don't blame them.
It was either they (literally) sell out or enshittify. Choose your poison. Hosting and running LLMs is an expensive business to be in. There wasn't ever going to be a good ending to this story. The original investors need to be made whole.
What’s with all the big acquisitions recently? Is it advantageous for some reason to announce all of this stuff now?
The VC capital for AI is probably drying up. Now the question is: who will buy OpenAI and Anthropic?
The public
Not if they can't indefinitely contain ram and SSD procurement. And they can't and the Market already showed with specex that they are unwilling to float these fly by night outrageous 'investments' onto institutional holders.
Institutional holders mass revolted at spacex getting into the basket.
AI costs more than having people do the work. Q2 CFO reaction proved that.
No, its just the final stage of the bubble before it all comes crashing down. :)
is this a leverage?
https://openai.com/index/hugging-face-incident-and-the-road-...
Not good news and in the long run this circular move will fail for them. What are the alternatives?
So is the next step to just basically create a cloud business.
they basically own chips - data centers - discovery etc?
Forgive me for newb question, but why Hugging Face is a thing at all? Couldn't models be simply distributed via torrents? And the whole aggregator thing would come down to indexing magent links published by model providers?
Why is any file hosting service ever a thing at all, when literally any file can simply be distributed via torrents?
There's a herding effect with torrents where popular things are quick to get, unpopular things may be very difficult to get, because the majority of users delete files to save space.
I might host 3 or 4 models that I've downloaded recently, but I won't be hosting the 50 or so that I've tried in the last two years.
And who seeds it? If you're going to pay a host to seed it, they might as well just provide HTTP and let you add them as a web seed to your torrent, which we could be doing already.
But if you don't pay a host to seed it, either the host's business model won't play well with torrents, or there's no host and a torrent will rot.
(It was a retrospective question.)
Torrents are unreliable, also for an agent or script it's easier to just do wget model
Then someone would still create a website with an index of all the open models. Where people discuss & rank the models, show related models, ...
And now you've recreated most of HF
Why don't we use message boards instead of Google? Couldn't websites be distributed via direct DNS requests instead of Google serving links?
You are not the first or 100th person to come up with this idea. I don't really get it either but there must be a reason it hasn't really happened.
The important thing about HuggingFace isn't the safetensors files, it's the READMEs and the Google search placement. It's easy to reproduce their distribution with torrents, it's very hard to then establish yourself as the default option.
It would be far more efficient to decentralize the data. But HF provides convenience, they subsidize the cost. They gained millions of users, and many enterprises. They can now sell the popularity of their platform. Nobody can buy a p2p network of people.
Very "why would anyone use Dropbox when I can setup a SFTP server" vibes.
Or even “why would I pay for a flight when I can simply walk across the country”
It’s all about the convenience, minimising the time and effort from “looks interesting” to “running the model”.
Nvidia don’t care if you do it on their cloud, someone else’s cloud, or on your own machine - they win either way, as it further propagates the technology on which they are building their future.
Torrents aren't that scary. If you have the patience for local AI you can figure out qBitTorrent in less than an hour.
Torrents are trivial. Each individual bit is trivial. But being able to click a button that says “run model” is even more trivial.
> Forgive me for newb question, but why Hugging Face is a thing at all?
Because you can't host arbitrarily large files on github, it's basically become a defacto "publish your project here" thing.
For a CN domestic equivalent take a look at Modelscope.
Well, ask yourself: "Why am I on Hacker News?". You could just "as easy" use free / opensource alternatives like Lemmy, Mastodon, etc.
beating the dead horse after other dozen comments, but the same reason we use github / gitlab instead of using Savannah
hugging face is basically a real easy way to run llms. They also provide a bunch of libraries to do things like split compute across all your resources.
Looks like owning the hardware wasn't enough and they want to own the ecosystem as well
No, what? Did they just do this to make Chinese models harder to acquire outside of China?
They will just download them from modelscope
Congratulations to the Hugging Face team!
The suits are taking our toys! Scary!
Great for Nvidia. Bad for the rest of us. Oh well, so much for hugging face.
Nvidia is protecting their investments. Now Huggingface won't sue OpenAI for the hack. That will get swept under the rug.
There are a lot problems with this post - Only "The Information" is claiming the deal's done. - Neither CNBC, Reuters, Techcrunch nor the Business Insider post whose title is cited do more than reference The Information's paywalled claim - Only TC _even mentions_ the potential ~$13B deal on its homepage - Not even a mention on Lobste.rs
So, this is the end?
A dark shadow moves over the meadow…
I wonder if OpenRouter being acquired was a catalyst for this deal.
I have never seen an acquisition be good for the users. I struggle to believe this one will be different
I'm sure it'll be fine. As long as you have the latest 90-class card you'll probably continue have nearly full functionality from the HF libraries. (Upgrade to enterprise gear for full functionality)
The fit is theoretically good (nvidia is model agnostic) but I can see then pushing the ecosystem increasingly towards cuda and some custom nvidia software packages for inference etc etc
Is huggingface profitable?
I'm not a fan of big-tech acquisition results either, but one benefit can be that a product continues to exist when it would otherwise become insolvent.
Truer words were never spoken. This is painfully true.
Apple buying Workflow (became Shortcuts). Its users have a better, faster tool and got it soon after acquisition. And it has many more users now.
Was Workflow available on every platform running on every hardware provider?
I’m not sure your point, sorry.
That specific example might be relevant to the case "I don't see any acquisition being good for the users", but not for the specific case of the HuggingFace buyout. Workflow was already operating within the bounds of the closed Apple ecosystem. Huggingface is providing models not only for Nvidia chips but for their competitors hardware (Apple Silicon, AMD GPUs, ...).
I think that it was already iOS only, so making it free was just flipping a flag etc. I'm not sure how that helps his point tho.
I was not making a point. I was trying to clarify the example.
But after the answers, I do think his example is poor. Models available at HF have many purposes and will run on many platforms. Commenters here are suggesting this will no longer be the case.
Whereas the example Workflow (iOS only) -> Shortcuts (iOS only), there was no change in that regard.
I see; thanks.
Acquisition of GitHub let to increased downtimes, but also to unlimited private repos for the free tier.
The unlimited private repos for free tier would have happened anyways. You have to remember that this was around the time people were jumping ship from GitHub exactly because they didn't offer private repos for free. It was something many wanted, and they were actively seeking out other places that would give it to them.
I'm not convinced that's the case. GitHub was like that forever, they were well established and the change happened not long after Microsoft bought them. There was no global shift to gitlab instances or Atlassian as far as I am aware.
You can dislike an entity or an action and still acknowledge it also had some positive effects.
Overall GitHub still got significantly worse since the acquisition. Downtime was essentially zero before.
Usage was 5% of what it is now before.
It was unreliable post acq. and before the slop-tsunami, the latter has just multiplied the underlying issue of their ipv4 only half assed azure migration.
... Which gitlab already had before github. And still does.
Yeah I'm afraid they will only keep cuda support for their software. Good thing it's all Open source
Nokia buying Qt in 2008 brought an LGPL option.
Alibaba's Modelscope like it.
Is there any cash involved or is this all stock?
What a farce, this whole thing.
Brilliant replacement of http://build.nvidia.com to increase developer reach and deployment of nvidia open models!
Its becoming impossible to track all the acquisitions.
I honestly feel like we centralized too much on huggingface same as github.
Is it because OpenAI hacked it? :)
Nvidia has already a good free offer with Nim and a lot of compute power available. Plus, they obviously have interest in spreading open models culture.
I'm more worry than positive tbh.
That’s a lot but if it makes people happy.
Nvidia overpaid for Hugging Face.
Monumental implications on OS
Can someone explain how this works? Huggingface serves enormous files and therefore presumably must pay huge cloud fees. As the dot com joke goes, they make a loss on every transaction, but don't worry, they're going to make it up in volume.
I’ve asked ChatGPT etc a few times how Hugging Face makes money. Never quite got to understanding . Good for them.
You could just go to their website and look at the pricing pages? Why are you asking an LLM?
Because I never ever see anyone talking about using it, except for occasional reference to weights.
Gemini did a good job of explaining it. fwiw, it may have helped that i accused Gemini of leading me to a "scam site" like "mega dot com"
We keep talking about EU having to be more present in the AI race, but if the lifecycle of European AI companies is to be bought by US ones, what’s the point?
nvidia antitrust incoming
china have different sites for models storage.
Letting a hack go without pressing charges has never been so lucrative.
13b Jesus christ
OpenRouter->Stripe (~$7B)
Hugging Face->Nvidia ($13B)
Keep an eye on Exa. With local models and niche harnesses proliferating, they're going to need a way to search without everyone having to run their own index.
Google is an obvious buyer if they could get it past regulators. A Doubleclick-level addition of the agentic stuff they're bad at to the indexing they're good at.
Nvidia is the obvious less conflicted #2
Secret third option: Cloudflare. They're already the glue for so much of this stuff.
What has open in tech become now?
Just in recent weeks Openrouter bought out by Stripe and now hugging face bought out by NVIDIA.
Is this really freedom and choice for consumers? No it’s the proliferation and nomination of big tech.
Best case scenario
You're running the leading website to the future of LLM and Ai and you decide to Nvidia. All for $13bn, folk don't understand money.
https://en.wikipedia.org/wiki/Market_foreclosure
This acquisition should be blocked (and never will sadly), they now have both the incentive and the ability to influence a platform that's supposed to be hardware agnostic (and built trust over that) toward CUDA stack
Microsoft did the exact same with github, acquired stack agnostic platform, and turned it into a copilot/azure one
Congrats to the team. I have a strong feeling this will go down in history as one of the last great exists before the bubble bursts.
12-24 months from this acquisition will likely look like a crazy burn of capital and cash.
Time to fork it and build a new place for true open source.
Good timing
Boy, there sure is a lot of money flying around...
First they came for all the dev tooling - uv, Cursor, etc. Now the routers and providers - Open Router, Hugging Face...
Who or what is next? And what is the endgame I wonder??
Seems a bit high
Wow, nice strategic move and price seems a bit low tbh. Good deal.
Well, there goes the neighborhood. This is why we can’t have nice things.
I wanted to pray for AMD to attack somehow but then I remembered their owner CEO's are cousins. Should we pray for Chinese GPUs?
Oh jeez
Big Wolf buying the sheep farm. Nice
Oh no. I use huggingface all the time. Sad news.
I really wonder why Nvidia would do this.
Why would the most rich and evil company on the field want to own a practical monopoly?
Keep alive the on-prem hardware sales? Not as big part likely but still something good to have. On-prem hardware needs models to be available to be useful. So pushing those could sell more on-prem hardware.
Ai companies are making their own chips, Apple unified and other unified ram solutions also a threat
Nvidia is making tons of money by selling GPUs at a very high profit margin. They will do anything to remain dominant
Owning the roots, the trunk, the branches and the tip of the leafs.
Big money buying up open source. This has never gone wrong, nope.
Let the enshittification commence.
welcome nvidia :)
not even 27b :C
They dish out a gazillion money. It's like a gold rush.
Meanwhile, RAM prices still go up. I want my money back.
Nothing like a good old Oligarchy going as planned
Just like that they lost their ethos. AI oligarchy in the US is now cemented.
The incest is real
whoa
DISASTER.
Licensing. (And there is no 2nd Amendment for this one)
This is huge!
I really can only say: Fuck
models being pulled in 3... 2... 1...
dunno why this is being downvoted (check back in six months)
s-1.site
I really wish I'd done better bookmarking back when Nvidia was talking about acquiring ARM. There were all kinds of things coming out saying, if we do this, even though we will be taking over ARM, it will transform us from the inside out. We would become a new different company, that cares about something beyond our own self interest, our own chips.
This feels like a similar leap of faith. One that is hard to believe in. Thankfully, I think Nvidia can keep the lights on here & keep this going. I don't think they have to do much, per se. But it felt implausible then to image an Nvidia that gave a shit about anyone else, an Nvidia that actually gave a flying fuck about drivers or upstream Linux or ecosystems that weren't entirely within their own control.
Similarly the upper quartile of succes here feels mostly like benevolent neglect. I think we can hope for Nvidia to just not mess up a good thing, for them to understand that this open model open ai universe hinges upon Hugging Face, and for them to pretty please keep caring about the existential risk of the hyper-ai'ers all building their own properietary models on proprietary hardware and leaving Nvidia behind some day, and HF being the hedge against being left behind.
um um um um do we want nvidia to be on the same network as hugging face given the recent incidents?
could you elaborate on what happened?
https://openai.com/index/hugging-face-incident-and-the-road-...
Fuck.
the title of this post is misleading… “in talks” != not “agrees”
It’s not misleading according to the The Information piece (second link)
The story is in an intermediate state right now, but as semiquaver points out, The Information is reporting it as fact. Since their reporting tends to be as reliable as it is hardwalled, we went with their claim in the title.
I agree, “agree” is super weird
Anyone old enough to remember anti trust laws or even just laws?
Please don't post unsubstantive comments to Hacker News.
No doubt you have the nucleus of a substantive comment here, but that's not enough. If you only post the shallowest top stratum of what you're thinking, other people do the same, and then we get "Laws are for poor people" and endless descending repetition. The whole point of this site is to try for something other than that.
https://news.ycombinator.com/newsguidelines.html
p.s. Also, please don't be snarky on HN. That's also in the guidelines.
This is the last time I will engage in self promotion for a while but the above comment and some of its replies are a perfect demonstration of my latest guidelines violations project… https://classify.stylometry.net/violations/49458425?threshol...
I'm sorry I haven't responded to your email yet! It's in the queue...
You are right but its the initial shock on bad news, hopefully this will spawn alternative competing services.
I thin HF holds huge power in how they’ve consolidated all the open models and data, but monopoly feels like a stretch here. They are in reality a fairly small startup with lots of alternatives (all of which are much worse at this point granted) and are mostly a loss leading part of the open source ecosystem. I think it would be very hard to make a case against this on monopoly grounds, though I wouldn’t be opposed to someone trying if they thought it was possible.
The AI judge doesn’t have that feature yet
reminder of them coming soon!
Laws are for poor people
Is this why OpenAI tried to say they “hacked” them lol
tldr: the marketplace for opensource models became wide open
EU regulators...wake up!
I also see this as an antitrust case, but to see that, you need to be much more up to date on technology than anyone who decides such things.
It's comparable to the biggest bank buying the biggest ratings agency.
They absolutely should, but what would be their impact on American companies buying each other out?
If they want to operate in the EU, quite a lot. See cases against Microsoft, Apple for example.
OK, can you provide specific cases/articles about it? I'm curious what can EU do with a merger of companies that are not legal identities within EU.
It's different for their local counterparts, but the original companies?
Microsoft/Activision Blizzard was tough for Microsoft in the EU despite them both being US companies, because they affected European consumers.
Let's file an antitrust complain.
Not just on this HF acquisition, but on the whole ecosystem monopoly.
That's a great news for a few rich wallets and bad for all of us.