I think the difference between the Anthropic token maximization approach (vibe code all the things!) and OpenAI's focus on efficiency, terseness and token reduction are going to be the defining features of who wins the long-term race.
My money is on the more efficient solution. Even if Anthropic can win some benchmarks by using 3x tokens over 3x time, it is a terrible base to build toward the future. Users are no longer willing to wait exponentially long for linear improvements. And as we see from some of the Chinese models, they can quickly distill frontier models with the tax of being slower and more token-guzzling, while retaining most of the quality. The real differentiators are becoming speed and efficiency, which translate to cost and user velocity more than incremental capability improvements.
It's great that frontier models can solve complex math equations, but bread and butter LLM usage (where the money is made) has already shifted from "I need the best always" to "what solves my day-to-day problems quickly and consistently". Fable usage as a percentage is flat-lining. We are already at the point where output quality is negligible. What wins going forward is cost, speed, consistency and the compounding effects of "softer" improvements to the harness.
Not to sound like a mark, I try to not get attached to any of these providers.
I've jumped between copilot, claude, gemini and chatgpt since the start of the year. chatgpt wasn't even worth looking at early this year.
Anthropic has the smarter models for sure, and seems to be default in corporate. However, the amount of budget you get with GPT as a user is much better, the harness feels more polished, and the models are faster. They are also much nicer to work with, I can just read the output for the most part. With claude I get pages of text and need to skim to find where the actual information i need to care about lies. So much more cognitive overhead.
Sol is smart enough for anything I've thrown at it, it's not one-shotting like fable, but I'm more willing to actually go back and forth with it, and it's likely producing better output to keep a human in the loop rather than trying to solve the world independently and making multiple incorrect assumptions.
I think GPT sees the market changing and is correctly repositioning themselves. Anthropic is down the wrong road, and if they don't correct course quickly I'm sure many of those enterprise contracts will start pivoting.
> and it's likely producing better output to keep a human in the loop rather than trying to solve the world independently and making multiple incorrect assumptions.
I was just discussing this with a co-worker yesterday. I would really like a model (or harness?) that worked with me instead of for me. Walk me through its choices and decisions, let me correct it and guide it along. I would be way more confident in it's output, I would be more familiar with the changes that are being made, and it would make reviewing the final code way easier since I was making the decisions along side it. I'm sure it would also reduce the "brainrot" we're all going to experience the more we hand work to these models.
does "Superpowers" exist outside of the Claude ecosystem? I feel like I've become hooked on this workflow - honestly I could take or leave the models ... it's the workflows and the way that they essentially create tightly focused loops over multiple sessions that I've becoming fairly dependent on.
Aside from the skills mentioned, I recently found that asking the model to create a simple HTML presentation to walk you through it's proposed design can do wonders. Fine tune your prompt to your liking (language style, what to include, what not, etc). Then, read that thing thoroughly, and keep asking questions and iterating on the plan until you fully understand what's about to be built, and are happy with it.
I'm ok with that. When the.major AI players implode under debt, it will create a massive proliferation of folks who go on to start new businesses unencumbered by the debt and bad decisions by the current leaders.
The collapse of the massive overvaluation and circular investments will be the undoing of several major tech investors and companies that have a serious contribution to the things in tech we don't like. It will be bad for the economy, but it will also weaken the abhorrent control that those companies have over regulation in the United States.
It's gonna be a rough time, but it's pretty clearly necessary.
The only big problem is that if that collapse happens under the current administration in the US, they will be utterly incompetent to respond to a real domestic crisis, since they have been virtually unable to do anything without creating more problems.
I really would like to see OpenAI’s focus on efficiency but everytime I use Codex, it wastes tokens like there’s no tomorrow, hitting week limit in a day, where I’m able to use Claude just fine. Maybe it’s based on the codebase, I don’t know, but I have better results with Claude than Codex.
My boss uses opus and gets good results when I use it always burns tokens. The other way is also true too I get great results with sol/terra but my boss does not.
One of my challenges is that I often end up burning tokens trying to build the right solution rather than building a solution that is good enough and deferring the right choices until later. I have been actively working to change my expectations for building with AI to accept worse solutions to get things going rather than trying to solve everything at launch.
This has been a recurring problem for me - as a security engineer catasrophization is a fundamental skill to finding vulnerabilities in complex systems, but makes me to conservative when building. For some of my leaders they are much better at saying 'good enough, ship it, and fix it later'.
Maybe. But if Claude is fine with my prompts while Codex uses them as an excuse to burn tokens. I have nothing against the model, they are more or less on pair, it’s just that Claude is giving me more value for same money.
Codex is fabulous at work, where token use is near limitless and ultra-thorough tool use is welcome. Go ahead and fire off searches for look-alike terms on my 96-core cloud instance.
By contrast, Claude Code's bias to make assumptions of reasonableness about underlying systems has proven to be immensely frustrating over the last month or two, both personally and at work. I've wasted days on "that was my mistake. I've been reporting numbers on the old architecture because I hadn't enabled the new one in the config" both at work and home. It's immensely frustrating.
But here we are. Wrestling with energetic idiots in model form, wrangled by over-specific harnesses that struggle to stay off of deranged side-quests.
I had the opposite experience. Claude models and its harness feel like they are set to eat tokens for everything, especially if it’s ultracode effort. I have seen it spawn 6 agents and eat my 4-hour quota right in front of me. Codex is on point and follows instructions well even with max effort. I like my analogy of Claude being garrulous and Codex being laconic.
If I see more limit hits in same sitting session, I have to rearrange my workflows. my experiments with qwen and deepseek have been good, cant wait to try glm and other models.
Just before I canceled my 20x Max sub I had a day where I had ~15% of my weekly I was trying to burn. I set it on ultracode and because I had set the max agents 32 for another project and forgot, the five research agents ended up spinning up a total of 26 subagents and burned through the remainder of my weekly in the span of 20 minutes before I noticed and shut it down.
Claude did the same thing to me the other day. I ran out of my 5 hr limit, and it went into my $100 credit they had given me. Multiple parallel agents. It ate it in no time flat.
When I checked, all that credit was gone, I still wasn't into the next 5 hours, and all the agents had failed, returning nothing.
I didn't even get anything for burning all that credit. If I had paid for it, I'd be very, very pissed.
Similar experience here. I had raised my cap to $20 because they had given me promo credit. The credit expired without me using it and I didn’t notice.
One fine day I was like, oh my weekly quota resets soon, I will kick off an expensive bug hunt. It launched parallel things and burned $10 in like a moment.
Here is an excerpt from the system prompt for UltraCode (Same for Fable,Opus,Sonnet):
"Ultracode. When a system-reminder confirms ultracode is on, that opt-in is standing: author and run a workflow for every substantive task by default. The goal is the most exhaustive, correct answer you can produce — token cost is not a constraint."
You've articulated what I found unsettling about Boris' pov that "coding is a solved problem". I listened to a few of his talks and was instinctively off-put by that sentiment. I figured a fellow programmer would understand and speak on the nuances.
Granted it did make me think about my biases and to lean into more future facing inevitabilities. But you've nailed it, for Boris and Anthropic, they are betting that coding is a solved problem in the sense that any person can one-shot any random idea and the output will be in some abstract sense "good". And then at what cost and toward what end?
On the one hand it feels true. On the other I ask - what good software have anthropic, or anyone else, produced that was fully vibed?
As someone who does near 100% of my coding via LLM these days, i still find that for anything complex i am still looking at and thinking in terms of code. Im still quality checking and steering at some interval via code. And im still not sure how or whether i can replicate that level of thought without still dealing in code at times.
It's a scale thing. with one fairly simple Android app, it's doable. anything Enterprisey is a nightmare. maybe that's the lesson and the problem is not with the llms but with accidental complexity. Just right now I feel like I'm one mythical LLM minute away from the next clean pull request...
In this last week I've started reviewing code more and in just a short time, I've found 3 fairly simple things that were introduced by Claude that were not wrong per se, however, they were very inefficient and didn't address the root of the issue. I still think we're in a place where the output looks good as long as you don't look under the hood or keep it scoped to small, vibe-coded projects. Once you get beyond that it can fall apart. Anthropic must have a large codebase by now though. Yet I haven't seen much released from them about how they actually work day to day on development.
What makes you think Antropic has a large code base? what do they do exactly that would make them need a large code base? Or maybe the word Large can be understood in different way?
it'll all be centralized models justifying their capability against local inference in, maybe 3 years or less
once we have a bit more memory fab capacity and the insane bottomless investment in AI giants realizes there is a bottom, local hardware will catch up with model performance to the extent that centralized inference will be downgraded to special cases or for orgs that find it cheaper than buying expensive hardware
but really most power users are going to have 1 TB unified RAM and local models that will do well enough
for light office use you can still have a cheap laptop and a claude subscription
> My money is on the more efficient solution. Even if Anthropic can win some benchmarks by using 3x tokens over 3x time, it is a terrible base to build toward the future. Users are no longer willing to wait exponentially long for linear improvements.
As much as I wish you were right, everything about software economics for the last 30+ years has favored _less efficient software_. Traditional hardware has been optimized for traditional software for decades and we still see bloated software win consistently. LLM hardware is at the start of its cycle, with abundant low-hanging fruit to conquer--I would expect the pro-bloat dynamics to weigh even more heavily in the LLM space than in the traditional software space.
LLMs are already of sufficient capability that if they were super cheap and fast and made no progress on intelligence, we will still make huge leaps in our ability to build systems and solve problems.
I'm just happy there is capital behind the efficiency path because I am confident we can get positive value on that path.
Oh no, I use the top shelf models every day and I really think they have a lot of room to improve in pretty much every regard. I suspect Fable usage is flatlining because it's not that good comparitively and way too expensive.
Seems like it wouldn't be hard for Anthropic to tweak a few prompts or RL pipelines to tune for terseness and token-efficiency if that stays as something that consumers want.
I find it unlikely that there's some fundamental property of OpenAI's models' "personality" or style which Anthropic (or any other serious AI firm) wouldn't be able to match if they wanted to.
They are both on borrowed time. The only thing keeping them afloat business wise is that current hardware costs are prohibitive which keeps local models artificially constrained. The next era will be open weight / local model for the masses and SOTA for the big players.
If your prognosis is true I'm not sure it's fully positive. Inference without batching is just massive less efficient, even if local hardware can be more energy efficient per operation and can skip out on cooling.
Open weights, obviously beneficial. Local compute when not necessary, seems like it'd be significantly worse for the environment?
I think because more devs cant run things locally, we are not getting the "open source gains" that you would get by having the network effect of more eyes on the work. Theres still little nuggets of gold in there though (eg antirez's DS4 project). But once more people can get their hands on hardware, I think the flood gates will open. And once that happens, I dont necessarily think people will run locally. But that will enable fungible service providers which we already see, but at a much larger scale.
To a lesser degree, open weights also leads to an eventuality of these two companies not being able to sustain their capital investments. Not to mention their pricing models are unsustainable as they currently stand. So they are being eroded from the outside-in, while also trying to fight the internal pressure to continue to raise prices/margins.
EDIT: I actually think the harness is more of a future for these big players. And theres real value in providing a high quality harness. So maybe they move to SAAS for claude code in the future. Who knows
Claude used to be 10x more efficient.
I think there are no barriers of entry between one coding agent and the other.
Therefore, I expect them to reverse as soon as people switch.
At least this is what I will do.
If the problem isn't that hard, I've been using Cursor's Auto or Grok 4.5 (not 4.6, it's too slow).
They're both pretty damn competent and more important, Extremely Fast! I find the speed more useful than trying to be a hundred percent complete on every task. The big intelligent models screw up all the time as well, but I have to wait twenty minutes to three hours to find out.
GPT 5.6 is especially tenacious and seems to want to solve every bug in edge case 1000% all the time. Sometimes that's what you need, but a lot of times you're just trying to move fast and figure out what the product is.
There is no evidence regarding distillation. It is impossible to distill a model in just a month which was the gap between fable and Kimi k3. Anthropic wouldn't even keep up with the load. It is just another example of American exceptionalism.
“In one notable technique, their prompts asked Claude to imagine and articulate the internal reasoning behind a completed response and write it out step by step—effectively generating chain-of-thought training data at scale. We also observed tasks in which Claude was used to generate censorship-safe alternatives to politically sensitive queries like questions about dissidents, party leaders, or authoritarianism, likely in order to train DeepSeek’s own models to steer conversations away from censored topics. By examining request metadata, we were able to trace these accounts to specific researchers at the lab.”
—
“You are an expert data analyst combining statistical rigor with deep domain knowledge. Your goal is to deliver data-driven insights — not summaries or visualizations — grounded in real data and supported by complete and transparent reasoning.” (variations appearing 10s of 1000s of times)
Does Dario have the same relationship with the truth as Sam? (Their companies pirate books and develop products that compete at some level with those books’ authors, so obviously neither are that wonderfully trustworthy, so maybe “no evidence” meant you don’t believe this evidence rather than you weren’t aware of it. I would understand and respect your lack of belief!)
That's what any harness could do. By itself it's not evidence of distillation. Just mentioning Deepseek in there is just fear mongering, again American exceptionalism, which creates the belief only the US has the right to own cutting edge technology. It's a disservice to the entire world, and china happens to be the only challenger to that belief. They surely also asked for tasks to avoid mentioning Trump's involvement in the Epstein files and CP, but don't mention those, due to American exceptionalism. Dario has stated that he is an American exceptionalist. He powers Israeli/US bombings in Gaza, but only cares when China does the same.
This is evidence only if you're an American exceptionalist.
The source is just anthropic saying what they believe and not providing any evidence beyond what they say. No raw chat logs to analyze independently. That's American exceptionalism
Seymour Martin Lipset, a prominent American political scientist and sociologist, argues that the United States is exceptional in that it started from a revolutionary event. He therefore traces the origins of American exceptionalism to the American Revolution, from which the U.S. emerged as "the first new nation" with a distinct ideology, and having a unique mission to transform the world. This ideology, which Lipset calls "Americanism" but is often also referred to as "American exceptionalism", is based on liberty, individualism, republicanism, democracy, meritocracy, and laissez-faire economics; these principles are sometimes collectively referred to as "American exceptionalism".
As a term in political science, American exceptionalism refers to the United States' status as a global outlier both in good and bad ways. Critics of the concept say that the idea of American exceptionalism suggests that the U.S. is better than other countries, has a superior culture, or has a unique mission to transform the planet and its inhabitants.
Like, when I consider the Tuskegee Syphilis Experiments or MK Ultra, or Flock, I have bad things to say about them but American exceptionalism specifically wouldn’t cross my mind. Corporations anywhere playing a card close to the chest or even lying… superiority, exceptionalism, aren’t my top reference points.
Since America is the first new nation, and individualism is a core value, the antithesis, communism, presents a direct threat. It's true that china can then be seen as a threat. My problem is with this bit: having a unique mission to transform the world. As we see with the pax silica agreement, even though it's not the stated mission of pax silica, the people behind it were born around that idea since a young age. No frontier US models is open source. Dario did not say in his open source letter, that his concerns about china also apply to the US, even though both countries are using ai in missiles today. I am just tired of this double standard where something is only bad if china or some other country does it like Singapore washing or the Panama papers even though it is standard corporate strategy worldwide to use legal domiciles in a country other than your own for fundraising or tax evasion. When Google does it, names are assigned like the Delaware loophole, but are spread far less than Singapore washing or the Panama papers
Perhaps partially covered in the “Critics of the concept say…”
Certainly weird to think the US isn’t chock full of problems (even if historically some stuff has been neat, like bringing together cultures and developing nifty tech in Silicon Valley).
They are not paying billions anymore. They just switched to buying and then destroying books. Arguably that's worse than training off of Anna's archive which Chinese companies still do. This comment is another example of American exceptionalism.
You know that buying a book vs buying a license is a very different purchase right ? And it does not work legally this way . Stop spreading made up stories
Can you really hold them responsible for book burning when they’re being compelled to do so by governmental laws? Seems like you should be pointing your finger at lawmakers, if anywhere.
You pay royalties to your publisher . They monitor situation , if a model has unfair amount of context about the book they bring you to court . Once they win they spread some money between owners + keep some money to fight future violations on the scale since it’s profitable for book publishers.
It’s economically lucrative for everyone in that chain to attack again and again ai vendors , unless they are in China . In this case they can only cry .
Me? A lowly commoner without hundreds of millions to lobby them? Why aren't American ai companies doing so? Too busy training models? They're shooting themselves in the foot when they could just use Anna's archive and lobbying is cheaper than paying billions in copyright settlements. Oh wait I am wrong. Shredding and scanning books is much cheaper than lobbying to use Anna's archive. Still can't do anything because I don't have money for lobbying
That was a one time payment. Another example of America exceptionalism assuming its a periodic payment like paying rent. look how they give money to publishers who then give back crumbs to the authors themselves.
Who told you it’s periodic ? To find a stolen book in llm is very easy . And if you break same rules twice any judge will fine you more for that .
You break you pay .
That’s why in the western world you got book publishers . They have lawyers etc .
If you prefer Chinese way : laugh at anyone who is taking about copyright , whether that a book , a model , or manufacturing secrets in eu , us or whatever sure .
A family business of my friend in eu was destroyed due to stealing until every single bolt position design of their system by China . They had no legal protection .
Keep calling rule of law vs no such rules an American exceptionalism .
It's hard to put a number on it, but even accounting for all the time in meetings, talking with stakeholders and developers etc I'm over 10% more productive overall. I earn substantially more than $2000/month, the ROI is there
It's only expensive compared to the currently very strong offering from OpenAI. Or other models - my hobby projects are all on DeepSeek
What you’re saying is that they should be charging $2000 or more per month then.
Perhaps that’s true, but it’s a price tag that’s a lot harder to swallow for many orgs than $200/mo, and would require some hard justification for how your increased productivity contributes to the business bottom line.
I’ll agree that you can probably do that with hard numbers. I am skeptical that most $200/mo users could.
I think the rapid improvements in local models will make a $2,000/mo price point completely impossible to sustain. This feels like a race to the bottom.
yes and no, anthropic and openai are losing money on people who max out their sub, but openai has a lot more room to play with with much cheaper models to serve (by all signs we have from actual api/task pricing)
I believe it's been crickets because open-source/DIY solutions almost never become mainstream. Devs tend to think everyone wants a self-service to save a few bucks.
Most ordinary people don't care that much about privacy and if there is a solution that just works well enough to cover their needs and costs just fair enough to be affordable, they are going to use that. I feel like this is why fast food is such a thing. There are far better food options out there that either require a little bit more effort or money. Your post on Linkedin is akin to someone claiming in 1960's America that home-cooked burgers are the future, despite McDonalds gaining ground.
It is also why crypto wallets and the like never took off, people don't want to give up the convenience of a bank account, understandably.
I switched when 4.7 dropped, after over a year on the service. It was an immediate improvement - not even 1 hour before Codex was giving me better results with less effort.
Stick with xhigh rather than turbo for most tasks though, now that the Age of Abundant Resets seems to be well and truly over for good (and 5h limits are supposedly returning soon).
They're absolutely best in a chocolate-in-my-peanutbutter situation - I use them to adversarially review each other's changes and ping pong the branch back and forth - A makes changes, B reviews, B makes changes, A reviews. Together they're much smarter than either individually - anthropic models tend towards more creativity, openai models can get bogged down in the nitty gritty.
I'm getting to that point as well. Has anyone noticed that sometimes claude just seems way dumber on a random day? Like they're doing some internal tweaking? Also, I'm 100% convinced that it's verbose writing style is to generate tokens to make you hit your limit quicker. I have so many rules and it still talks in this bizarrely verbose, cryptic style where it's sometimes borderline impossible to understand what it's saying.
I haven’t had any issues with Fable or Opus code-wise, but the way it has started writing recently has almost become incomprehensible.
At the end of a long session it will start saying stuff like “There are smoke tests on the foundation-gates that are left for the cutting seam checks on these domains, which is genuinely your decision”
Never before the past couple months have I ever not been able to understand wtf it’s even saying lol
I was working on a project recently that required the attribution of a data source, and it added to the "licenses" page of the project something like "We use <blah> and per their terms we owe an acknowledgement of attribution to you, the user."
So in addition to the stuff it says in a session there's gobbledy gook that it prints out in copy as well.
Hahahaha I wasn’t sure if I was getting dumb or something. Mine finishes the tasks and then outputs paragraphs of that nonsense. But the code is great.
My subscription expires tomorrow. Had subscribed ~March, eventually ended up paying for the $200 tier. However, there isn't enough of a moat for me to keep spending $200 if the models aren't being helpful anymore.
The unnecessarily jargon filled language was already pretty bad, but the latest Opus/Fable also just didn't seem to go far enough when asked to look into something, often leading me in circles.
Yeah it feels like they tune or 'optimize' the models after release and they get less useful to me as time goes by. I'm most productive the first few days after a release. Noticed this since opus 4.6.
For anyone on the fence, I was a hardcore CC user since it was released. I made the full switch to 5.6 sol and Codex about a month ago.
It's the better experience. The limits are way higher (I almost never burn through my $200/m plan), and the output is better than Opus 4.8 (Opus 5 is completely unusable for me).
I had a very similar experience. The combination of Claude going down frequently and the hype around open source models was enough for me to swap my harness from Claude Code to OpenCode. Then it became trivial to test out different models, and now the rest is history. Currently using OpenCode with z.ai and Codex $200/m plans for all my work atm.
Also try a hundred bucks on Openrouter and experiment with the Chinese models like Deepseek, Kimi, GLM. $100 will last a good while, and it isn't tied to a single model or provider.
I burned though $50 on OpenRouter in three days, this is with selective model routing based on tasks/strict AGENTS.md. A Claude 20x sub running Sonnet 5/Opus 5 and light Fable usage gets me through the month. It wasn't even close even though I wish it were.
Agreed, it's not SOTA but I'm happy with the trade off. My preference is to use mostly local models and augment them with Deepseek. It's been a pretty great equilibrium.
I have the $100 plan on OpenCode Zen, which I imagine is similar. I burn through it ridiculously fast. I haven't run the numbers, but it felt about the same as an Anthropic $20 plan
As a counter point, I've been using CC since December and I've never really had any problems with it. It's always done exactly what I want it to and I continue to be blown away by its capabilities, regardless of which of their models I've used. I also almost never burn through my $200/m plan.
Yep, switched from CC to 5.6 Sol. Not using it in my day job (only side projects), but I can crank 5.6 Sol on Extra High "fast mode" and never have to worry about credits.
Not doing crazy multi agent swarms, but have yet to hit any limits during pretty intense weekend sessions.
During this period however they’ve released models which lots of people report to be significantly more chatty. Framing it purely as a promotion ending feels like you’re giving them a bit too much credit. I doubt it’s a coincidence they started this promotion a week before the release of 4.8.
I think running a model unsupervised in anything above medium is a sucker move to burn more tokens. The high effort models can be great in limited context, but unsupervised they too often end up navel gazing. High doesn't always mean smarter, but it always burns more tokens. Medium and low seem to be decent for day to day tasks.
I am not sure the supervision is the problem, it's more the way Claude is acting in general, taking initiative that could burn thousands of token in a second. Just today I ask it a small fix on a newly pulled project, it wrote 5 lines of code but then immediately started to run the full test suites, which itself runs in docker, with several images that I didn't pull yet so it started to download everything and by the time I click stop, it already filled the context windows with dozen of hundreds of useless lines...
I find it very hard to fins the sweet spot in the prompt between "do not assume, do not take initiatives" and "inform me if there is a simpler way to do what I am asking or if there are some downsides I may not have thought about".
> I think running a model unsupervised in anything above medium is a sucker move to burn more tokens.
What about errors compounding and any on-the-go decisions being made being the wrong ones? That kills anything long form, no matter how good and detailed your initial plan is - there will always be something along the way.
The models would need a way to identify a difficult problem and apply max reasoning there themselves and cruise through everything else at a lower level.
That’s my experience too, going off the deep end with CoT doesn’t meaningfully improve output on a lot of tasks but it does incinerate tokens and take longer
I add commands that constantly fall into this rabbit hole to AGENTS.md alongside an instruction for the agent to request escalation immediately instead of failing first then retrying out of the sandbox. It’s a hack, but it works.
I found the waffle reduced my overall usage. It doesn't matter much if it's smarter if it also needs more babysitting. It's quite good at making something quite advanced that is tangentially related to what you actually wanted.
As soon as it gets annoying enough to switch to another provider your Claude code tokens drop right off.
I was just gonna blast them for the infinite promo extensions and Fable, but at least they apparently have noticed this indecisiveness problem themselves and making it permanent is definitely the best way to solve it, lol!
After they perma-extended Fable into including it into the max plan, I'm willing to give them the benefit of the doubt with this one.
I've been watching this to see if they "extend" it again, let it end, or make it permanent. I'm regularly hitting 90-100% on my $200/mo sub and will switch to Codex in a heartbeat if they drop these limits. This constant uncertainty is really annoying.
"We hope to make this a permanent change to our plans, but strong demand for our models means that capacity may be tight over the coming weeks. We’ll keep you posted as things develop."
Seeing how many people with Max accounts on Codex are complaining, your in for a rude awakening. The days that Codex was the undisputed usage king, seem to have been reversed. Its been most most noticed after they did like 20 resets in a month and half, ...
They've been really struggling all of 2026. All of these "limited time" promos, just to have less usage than codex, and the shenanigans around "peak hour" reduction earlier in the year.
> As it extrapolates the current financial information and performance there is an implied assumption that the present financial environment will not change significantly in the future.
Yes, but their "run rate" assumes the current level continues unchanged, right? If revenue per month goes down then the projected run rate is optimistic. However, revenue has been increasing, so the reported run rates have underestimated revenue.
I think the better question is how much more than $65B/year revenue they need to cover what they are spending on capex and model development. I would bet money their revenue in the next year is over $75B (vs $65B), but also that their amortized costs exceed their revenue.
To anyone like me that switches between Codex and CC based on limits, but prefers CC to Codex, PI has been really great to migrate over. It can customize itself very easily, I was expecting to have to clone the repo or whatever, but no you can just tell it "add a manual mode where you present all changes as diffs in VSCode, letting me edit them or save to accept" and it will do it.
I wish I could use my Anthropic sub with it but I heard you get banned, but at least you can use it with any other subscription or model.
I got a max account during this promotion and it's been very fun but I'm a little burned out and am kind of looking forward to going back and tinkering with game engines without the help of an LLM for code gen (will still use it for documentation questions but I can do that with the free tier)
I too have the same experience with LLM generated code. I just get burnt out reading it and all the verbosity it has. I eventually gave up reading through it and keep it as a archive of previous work, while handwriting the code. If I get stuck somewhere, I asked the agent to generate a snippet based on my archived code and what i need to achieve and manually copy paste it.
I wish inline completions would have gotten better but it seems no effort is being put into it and it is frozen in time right now.
Thankfully, the stuff i use this code for is simple and small scale. I can’t even begin to imagine how actual programmers are feeling about this.
That is about the time I started using Claude Code as a paid account at any level. Previously I was extremely skeptical. Overall, it works and it has sorted out some things I would have probably let go for a lot longer especially with the markup on my very ancient website. Markup issues, template migrations, maintaining stringent preservation going back to HTML that was hand crafted in the late 1990s. I also learned quickly you cannot ask the magic 8 ball to solve things. You have to make it read, and plan, and then review and go back and forth with it. This can legitimately take hours. The difference is I can oft get most of the website modernized rather than just some of it following the more traditional methods. I've also seen how one can hit those limits pretty quickly, if they are going down from here that will make it less useful. And no way I am paying more on a usage credit basis. Prior to this, all my code work had been strictly with local AI as the inference engine and I can go back to that.
Edit to add: As a 3 month experiment, it has been positive. I have gotten things to work that none of the people I have hired and paid over the years took care of. And I myself have been too busy to prioritize. It's a useful tool, but only a fool would think it replaces the judgment of a professional. Not yet anyway.
I forgot this was in effect. I’ve been hitting my weekly rate limits two to three days in because of needing to steer Slopus 5 with Fable. Absurd that they’re being cut further in the face of steep competition from open weights models.
I think the better comparison point is Opus 5. I'm also using both and I think overall I like Opus slightly better, but I'm still using Codex a lot for any project requiring image handling.
I moved a while back when Claude started refusing to do security audits and also failed to run properly in my sandbox without a lot of wrangling. Renamed Claude.md to agents.md and had no problems at all. There’s almost 0 switching cost.
No. Here's a data point: I tried it for a few days. While it worked fine I didn't see any benefit to switching since it costs the same ($100) and I've spent a year getting up to speed on Claude usage and quirks.
Why, it seems like the supply is limited by the ability to provide, and the demand is limited by market alienation.
They raise their prices too high, a lot of customers will still buy but be unhappy about it, it's burning goodwill for money. If they drop their prices too low they have overwhelming demand.
They could be making money hand over fist for all we know. We don't really know how much compute is being used, nor how much it cost them.
A cautionary note. Your Claude account is tied to your email address, and it cannot be changed. If you lose access to your email address (I sold the domain), you cannot access your Claude account any more, you cannot change the email address, you can't cancel it, and the billing continues.
This happened to me, so far two months without any progress with Claude support trying to resolve it. Chatbot support got no response, email support got a single response after a month saying it had been passed on to another team to resolve. Mostly just silence.
I actually use claude these days mostly for mission critical tasks and code reviews. Everything else I use Sol. I have $20/month plans on both. For non-coding I also use Gemini on a $20/plan. So far I haven't had any issues but we'll see how things go. I have Qwen3.8-27B installed locally but until I upgrade my mac it's not for day to day stuff.
I’m supporting you as a company , but since grok 4.6 and codex , it’s just stupid to go with your pricing model . Cursor + grok + router that uses open ai and a bit of anthropic to verify tests etc it’s a no brainer .
Why should I pay you money , and have slower model and less intelligence? Oh yeah and I do not care about limits with cursor ultra at all . Unlike with you .
Cursor really is the best deal right now, the amount of usage you get with Grok is amazing and you can use frontier OpenAI or Anthropic models if you ever need to but most code can be written well by Grok.
It's not great if you don't want to use the Grok models though (and I don't, because it's now an Elon product), and if using Claude models via Cursor, the usage I get is way less, I was sometimes spending $60/month with Cursor and I get more with CC $18/month "Pro".
But CC took some getting used to, I also prefer the Cursor interface (the legacy "chat" pane).
Everyone says that you hit token limits after some time using either Claude Code or its web version. Even though GPT 5.5 is cheaper and doesn't impose token limits, it's just too non-nuanced. The only points for which I still stick to using Claude are these:
- I actually rarely hit the token limits using my $20/mo web plan (switch chats when the current one feels "bloated" due to huge context and therefore the token drain), which even covers some of my coding sessions using Claude Code.
- The visuals and "interactive" elements are still not introduced in GPT's web UI, unlike Claude's.
- The nail in the coffin is the fact that Opus 4.8/5 is just BETTER at doing my RTL verification review jobs than GPT 5.5.
I am not glazing the model; it's just a personal preference for getting the job done...
I have no idea why anyone would spend the money Anthropic asks for Claude models these days. There was a brief window in time when it was worth the money to use them a bit through GitHub Copilot, but there's no way in hell I'm spending that for Claude Sonnet when DeepSeek is basically doing all of my work right now.
Claude Opus and Fable are so bad compared to GPT-5.6-Sol it's ridiculous, their desktop client is worse, and the value is worse because OpenAI has been spamming discounts. They better get their shit together at Anthropic!
Edit: If you're mad I'm light on the details I have provided some in the replies.
gpt-5.6-sol uses fewer tokens and OpenAI has been more generous with usage, but quality-wise I wouldn't say they are inferior to each other.
I have a Claude Code and OpenAI subscription so that I can use Opus/Fable/gpt-5.6 as I please, and the models are often catching things the other models missed. So much that I would significantly weaken my workflow if I dropped one subscription.
My best workflow at the moment is to create the initial plan with Fable (before review/revise-cycling with other models). From my own testing it seems slightly better at arriving at high-level ideal solutions after sweeping the whole project, projecting future needs, then coming up with good trade-offs like "by construction" correctness.
While mostly subjective, maybe the closest objectivity I have here is noticing fewer revision cycles needed with Fable-initialized plans.
For personal projects, I defer almost everything day-to-day to the models, so it gives me a good feel for what the models are good at.
Even then, it's kind of a wash these days between the sota models, and we're talking about maybe a 10% performance difference or something. But every once in a while there's the experience of one model spinning its wheels on a bug/repro/issue while another model comes in and one-shots the solution.
That make sense. Let me ask you this
When the project reaches a level of complexity . Do you simply reach for better models or do you reengineer it or does the project scope stop at the egdge of the model's capabilities.
I am asking because in my personal projects after a while they becomes a giant messy ball of wires and i basically trust the model to untangle it for me , by the time it untangles properly, I run into my token limits.
With Opus 5 / Fable / gpt-5.6 you can simply ask them to fan out subagents to look for ideal architectural simplifications and rank their findings by impact vs confidence.
You can swap out "architectural simplification" with performance opportunities, bugs, correctness, etc. I get the orchestrator agent to then itemize it all into a file where I can keep track of which ones I've implemented.
The results are pretty astounding. I run these right before my weekly limits reset for each subscription and the findings will dictate the secondary tasks I get done during the week.
It's definitely token-heavy. I'm on the $200/mo Claude Code sub and the $100/mo Codex sub.
But it's pretty clear to me that software engineering is more or less solved and all you need is enough patience + tokens to get what you want. I think 20 years of engineering experience more lets me save on tokens rather than unlock things nobody else can build.
An example of the scope of one of my AI-engineered projects is a iterm2/ghostty-like terminal app that implements its own pty session, parsing, rendering. It's almost 2000 commits right now.
That said, I have a specific workflow that isn't just a blind "ok now make it so a screen can be split into panes". I have a plan phase focused on coming up with ideal invariants and such. But I'm not sure anymore how much of that is useful vs just yoloing a solution and then paying technical debt in sweeps, like garbage collection.
But the example you give is of a terminal for which there are copius examples in open source code. How hard is it really for a pattern matching machine to do that?
If I was doing it I would start by forking an existing repo and I might even say then that "software engineering is more or less solved since the open source revolution"
Pretty much every software problem we work on breaks down into steps that are solved in prior art.
Even if it weren't, if you're capable of explaining the context and constraints of your problem, then a modern LLM with effort=high will generally come up with a solution that's worth starting with because it's well-reasoned.
Moreover, you can start with the solution and then course-correct based on future information because refactoring is trivial with an LLM, yet human projects often ratchet into a local optimum because refactoring is too expensive.
I don't think "it's been built before" does as much work as it seems. I didn't fork a project. The LLMs reasoned about how to build the project from scratch using trade-offs that made sense for my needs, and they made reasoned, unsolicited deviations from kitty, xterm, and co, not just blindly doing what some ref impl did. Btw, it was still a lot of work because my project isn't just "kitty but swift".
Then the models went on to drive a well-reasoned incremental implementation of a system that lets me use the terminal running on my Macbook from my iPhone over tailscale with a decent scheme it came up with itself.
The point is that I don't really have to know how things work to build good software with modern models. LLMs can do things like read Linux source code and adversarially refine ideas such that the final idea is a good one. And my biggest influences on the project can be automated through the use of reusable markdown files.
Now, I'm at risk of downplaying all my years in software here, but I see the writing on the wall. It was only one year ago that I only trusted AI to do autocomplete.
Every time I try to use a lower tier model like Terra or Sonnet I regret it, so I just use the best one the first time to keep my sanity (it sort of works). Same with effort, you gotta just max it out (though I stopped using Ultra/Ultracode) and I never use fast because I'd rather work in parallel on more than on one thing faster almost always.
In general, many of these stories of "one one shots it and the other spins on it" is down to trajectory divergence and can be achieved simply using another instance of the same model.
While just simply trying many times independently gets you the improvement that is due to pass@k vs 1, you can get huge improvements if on top of that, depending on your setting, you find a way to ensure some stochasticity by perturbing tool calls, etc and running multiple instances.
The general theme is, embrace the stochasticity rather than the leaky abstraction on top of it.
With modern LLMs, investing in this kind of harness tooling is much more fruitful than hoping for the best from the model.
While many basic instances of this are built in to the popular harnesses (much of cursors higher-than-usual success rate with older models was due to really excellent context mgmt), you can never beat one that is optimised for your particular codebase, infra and general setup.
Until last year or so, the context management needed varied too much at too coarse a level across different models and even model instances, but now they are all extremely robust in a much higher % of contexts and are thus way more amenable to developing context management tools for, without needing to do a research teams worth of evals.
Custom evals and harnesses are thus extremely high ROI now. We are finding companies needing to do less and less tweaks and getting much fewer regressions (you should have reg tests in ur evals) with every new usecase and every new model.
It can be really simple to start with: change your grep/rg that it uses to a script that does in effect "rg $@ | shuf".
More complex examples are: giving different subagents different tools, randomly failing tool calls, truncating file reads randomly, having a small model invent N possible failure modes causing a bug and appending that to N prompts and starting subagents from each - this all forces each to pursue different paths. $example_specific_to_your_company_setup is highest ROI though, since most companies actual failure modes are dominated by idiosyncratic API shapes and retrieval quirks that no usual harness will bother modelling.
Also important IMO to not assign any meaning or semantically interpret the CoT as an acceptance mechanism (it is ok to use it as a rejection mechanism e.g if you see it plotting a sandbox escape whether it eventually emits the exploit or not is not something you want to hedge). We have to resist the temptation and ensure we only interpret tool calls, codegen, etc in our evals and only think of the cot as "some output that pushes the conditional distribution" which may or may not semantically match the typical preceding tokens of the desired tool call.
Sure OpenAI has open source tools, and equivalent or better models, and lower prices, and they get along better with other agentic tools, but Anthropic has much better marketing and I guess that's what matters.
I don't know why this comment's getting down voted. It's absolutely true. I would also add that Anthropic seems to limit, compute, the more you use it because I'm on the Max subscription, and it just stops working for me.
I'll ask it to do something and it'll say, I tried, but I couldn't do it over and over again or some variation of.
But it doesn't do that at the start of my subscription, so...
The thing is, is it's not a subjective thing. It's objectively bad. I think that's what the story is or the appeal of the post. It's calling out, something that everyone else thinks is so great, but it's actually really pretty bad compared to the competition. Trust me, I used to want Claude to win, but it's not.
Huh? Comparing model quality is something everyone is constantly doing here. If you need more specifics, it speaks in an incomprehensible way, stops working lazily, does a bad job and misses things constantly, and makes a lot more mistakes. I have both a $200/mo Codex and Claude subscription and swap between them when one runs out, and I'm always more miserable when I have to use Claude.
The Claude desktop app is also widely panned, as I mentioned, and for me this mainly is due to general UX and a poor remote control interface. Codex's connected machine support is top notch.
Because "$X is bad" is boring, especially when it comes to LLMs. I use Opus 5 and it's fine. It's more chatty and sometimes a little more difficult to steer than 4.x was, but I've found the code quality of 5 to be much higher.
Everyone has different experiences with these things (for example, I've never experienced what you describe), and "$X is bad" is not conducive to thoughtful discussion.
The issue isn't whether it's fine, it's that both Fable 5 and Opus 5 are worse to use for the job of programming than Codex-5.6-Sol in my experience. I am directly comparing these top tier models every week in my work, and many friends have left Claude in favor of Codex recently because of Claude's poor model quality.
One thing I do like about Claude is that the normal (non-Code) chat interface supports MCP, whereas ChatGPT basically does not.
This is just the cycle. If the OpenAI offerings are better and cheaper, people will shift there and then those discounts that made it such a deal will evaporate. Anthropic or someone else will entice people back with the discounts.
I suspect the net result will be that more Pro $100 subscribers upgrade to $200/mo. If you explicitly do simpler stuff with Opus, you generally have enough Fable time for most programming and planning tasks.
The 'tokenmaxxing' and the extreme gambling fiesta with Anthropic's latest Claude Code slot machine engine called 'Fable 5' which has given many subsidies and free spins of the wheel and cheaper tokens are all incompatible with the desires of their future owner: Wall Street.
If Wall Street sees a single outage or a tiny drop in usage, they won't be happy and will pressure Anthropic to take away the free tokens.
Better to reduce the limits now rather than to wait until Wall St. tells them to just to avoid a stock punishment.
This is a very bad time for them to be doing this when other plans are being very liberal and catching up to Fable. I predict they will revert this decision once they see their sub numbers drop.
As we speak, Claude is down. I was already complaining about how extremely slow and dumb it has gotten since Opus 5. I guess this will be the last nail in the coffin for Claude. At least for me.
I saw this announcement when it came out and completely forgot about it. That explains why Claude Code felt so surprisingly generous these past few months.
So their only answer to DeepSeek V4, Kimi K3, GPT 5.6 price cuts on Luna (80%) and Sol (50% on OpenRouter) is to temporarily extend usage limits, then keep extending past the deadline every two weeks because they still don't have an answer. May through August, that's like 5 years in this industry and speaks volumes.
The whole thing seems pretty opaque. I have a personal Pro subscription that I'm using exclusively with Claude Code on personal projects. I have no idea how close I'm currently getting to any limits, or whether that will start happening tomorrow. Nothing I've been able to find has really clarified it either way.
I've been using it on a few personal projects and run into the limits quite often. With Sonnet on high, I often hit right about the 5 hr mark when it resets. With Opus, I'll hit sooner.
I'm kind of surprised that you haven't been watching it with /usage to see where you're at. I've had a couple times that it ran out and lost what it was doing and had to start over, so I've gotten more careful.
And the time it burned $100 credit (that they gave us) and the fizzled with multiple agents, leaving me nothing of that work... Well, that was certainly instructive.
Then you'll probably also like /statusline too :D You just give it instructions on what you want to see down there, and it'll set it up. I like the model name and context.
I've never wanted to punch a meta physical entity in the face more, than I do Claude. I realised a lot of the AI context fatigue was from having to try and comprehend the absolute ridiculous wording. I cancelled my sub a while back (obviously).
I have both chatGPT pro and Claude max accounts and I am considering switching Claude for Grok. Despite all those claude hypes, for me personally, claude just does not match codex in almost all tasks, both coding and non-coding.
I don't know, we've been the tiny hamsters in the biggest A/B test ever, I'm possibly very tired of the token/limits game. This is clearly not how this can be monetised (if that's even possible)
Meanwhile every time their servers go down, your caches go down with it and you can pay for your entire context again. This sucks even harder when you like to use parallel subagents.
consumer hardware is moving towards local ai and the models you can run now locally are already at opus 4.6 level. within 3 years most pc's sold will be ai computers.
People take much more time off during the summer in the USA than during other times of year. It’s somewhat regional, but it’s been true in all the place I have lived. Probably July is the most common month though because in some regions schools start sometime in August. It’s not uncommon for people to take 1-2w off during that period. More than 2w often requires extra approvals, so is less common.
Ah, forgot about that. I was questioning if I should switch my big subscription to ChatGPT (was on the 20$ Open AI and 100$ Claude), seems like a no brainer now
Same here Fable has been thrash on my 5x Max, it's definitely been quantized, but not through API which is 10-20x as expensive.
So yeah, different people get different quality. I wouldn't be surprised if it calculates a wealth level, willingness to upgrade, influence, usage levels, etc. and decides what models to serve.
It's extremely obvious to me they've nerfed all models on my 5 Max from Fable to even 4.6, but i've tried through enterprise with huge differences in quality, and i've seen other people experiencing this both on reddit and twitter.
Advanced mesh manipulation, shader writing and editing, 3D math, spatial awareness and analysis. It's not just better, it's the only model that straight up works (sorry for the claude speak). A league of its own.
Don't take my word for it, use a simple prompt of "create a shader showing [complex scene]" and see what the other models vomit out, including opus 4.6/4.8/5 and 5.6 sol (compare fable low effort with sol xhigh).
Vehicle physics/dynamics in my case and yes, same. I got a lot of mileage out of letting it use Opus/Sonnet sub agents for much of the exploratory and implementation work, which cuts down on token use. I got into way fewer "oh, that's nonsense? what about this then?" loops with Fable and it was the first model that actually tried to reason about the full system rather than fixating on details and chasing bits and pieces out of context. Haven't tried Sol yet but so far haven't had a reason to switch.
No need to switch as they give out free trials and Sol Is available on the 20$ plan. It's very fast for its power. I ask it for insight, read the responses myself, and offer its points back to Claude. More efficient than letting them talk to each other.
Tbh the extreme discrepancies between very confidently made statements about "X is better than Y" a sign a to me this is something where peoples' biases are out of control. Not saying you are wrong. Just that these things are so hard to evaluated apples to apples and that things like under-the-hood routing changes muddy the waters so much that it's really hard to get reasonable assessments.
My tests are very visual based and easy to notice when the seed/temp or the routing or the A/B test comes into play. And it's been months of working with these models so comparison is straightforward and robust. Fable is the first time I can use AI to code with good results while everyone has been doing it for ages before me.
If Anthropic doesn't figure out why OpenAI is eating their lunch, they're in some trouble. I'm guessing they already know why, but aren't able to accept that they won't somehow come out #1. Or in fact they really believe they will still come out #1. Delusion?
This is ridiculous neither Netscape nor Yahoo made much money (source: I worked at Netscape). Anthropic is one of the largest fastest growing businesses of all time.
Quite a number of the smartest people I know got scalped to work at OpenAI. I don’t know anyone who went to Anthropic. Something I think which is under emphasized is that OpenAI has the human capital in addition to the financial capital advantage over Anthropic.
Over the long term I think OpenAI will produce the better experience when it comes to model quality, harness quality, and availability. I have been using codex the past few months and never looked back.
I think the difference between the Anthropic token maximization approach (vibe code all the things!) and OpenAI's focus on efficiency, terseness and token reduction are going to be the defining features of who wins the long-term race.
My money is on the more efficient solution. Even if Anthropic can win some benchmarks by using 3x tokens over 3x time, it is a terrible base to build toward the future. Users are no longer willing to wait exponentially long for linear improvements. And as we see from some of the Chinese models, they can quickly distill frontier models with the tax of being slower and more token-guzzling, while retaining most of the quality. The real differentiators are becoming speed and efficiency, which translate to cost and user velocity more than incremental capability improvements.
It's great that frontier models can solve complex math equations, but bread and butter LLM usage (where the money is made) has already shifted from "I need the best always" to "what solves my day-to-day problems quickly and consistently". Fable usage as a percentage is flat-lining. We are already at the point where output quality is negligible. What wins going forward is cost, speed, consistency and the compounding effects of "softer" improvements to the harness.
Not to sound like a mark, I try to not get attached to any of these providers.
I've jumped between copilot, claude, gemini and chatgpt since the start of the year. chatgpt wasn't even worth looking at early this year.
Anthropic has the smarter models for sure, and seems to be default in corporate. However, the amount of budget you get with GPT as a user is much better, the harness feels more polished, and the models are faster. They are also much nicer to work with, I can just read the output for the most part. With claude I get pages of text and need to skim to find where the actual information i need to care about lies. So much more cognitive overhead.
Sol is smart enough for anything I've thrown at it, it's not one-shotting like fable, but I'm more willing to actually go back and forth with it, and it's likely producing better output to keep a human in the loop rather than trying to solve the world independently and making multiple incorrect assumptions.
I think GPT sees the market changing and is correctly repositioning themselves. Anthropic is down the wrong road, and if they don't correct course quickly I'm sure many of those enterprise contracts will start pivoting.
> and it's likely producing better output to keep a human in the loop rather than trying to solve the world independently and making multiple incorrect assumptions.
I was just discussing this with a co-worker yesterday. I would really like a model (or harness?) that worked with me instead of for me. Walk me through its choices and decisions, let me correct it and guide it along. I would be way more confident in it's output, I would be more familiar with the changes that are being made, and it would make reviewing the final code way easier since I was making the decisions along side it. I'm sure it would also reduce the "brainrot" we're all going to experience the more we hand work to these models.
Those exist and they're called orchestration skill frameworks like Superpowers, GetShitDone, etc.
does "Superpowers" exist outside of the Claude ecosystem? I feel like I've become hooked on this workflow - honestly I could take or leave the models ... it's the workflows and the way that they essentially create tightly focused loops over multiple sessions that I've becoming fairly dependent on.
Yes, Superpowers is just a set of (agent agnostic) skills that you can use in any harness.
Aside from the skills mentioned, I recently found that asking the model to create a simple HTML presentation to walk you through it's proposed design can do wonders. Fine tune your prompt to your liking (language style, what to include, what not, etc). Then, read that thing thoroughly, and keep asking questions and iterating on the plan until you fully understand what's about to be built, and are happy with it.
the "grill" skill from matt pocock is quite nice for this
> I think GPT sees the market changing and is correctly repositioning themselves
I'm not sure how they'll survive their creditors tbh
I'm ok with that. When the.major AI players implode under debt, it will create a massive proliferation of folks who go on to start new businesses unencumbered by the debt and bad decisions by the current leaders.
The collapse of the massive overvaluation and circular investments will be the undoing of several major tech investors and companies that have a serious contribution to the things in tech we don't like. It will be bad for the economy, but it will also weaken the abhorrent control that those companies have over regulation in the United States.
It's gonna be a rough time, but it's pretty clearly necessary.
The only big problem is that if that collapse happens under the current administration in the US, they will be utterly incompetent to respond to a real domestic crisis, since they have been virtually unable to do anything without creating more problems.
I just need a Sol translator to sit in front of Fable and Opus :/
The Opus-human patois is unbearable
Opus yesterday produced this gem: "Standing where it stood." I replied, "never stop stopping!" and we had a stalemate, lol
I really would like to see OpenAI’s focus on efficiency but everytime I use Codex, it wastes tokens like there’s no tomorrow, hitting week limit in a day, where I’m able to use Claude just fine. Maybe it’s based on the codebase, I don’t know, but I have better results with Claude than Codex.
It might be your prompting.
My boss uses opus and gets good results when I use it always burns tokens. The other way is also true too I get great results with sol/terra but my boss does not.
One of my challenges is that I often end up burning tokens trying to build the right solution rather than building a solution that is good enough and deferring the right choices until later. I have been actively working to change my expectations for building with AI to accept worse solutions to get things going rather than trying to solve everything at launch.
This has been a recurring problem for me - as a security engineer catasrophization is a fundamental skill to finding vulnerabilities in complex systems, but makes me to conservative when building. For some of my leaders they are much better at saying 'good enough, ship it, and fix it later'.
Maybe. But if Claude is fine with my prompts while Codex uses them as an excuse to burn tokens. I have nothing against the model, they are more or less on pair, it’s just that Claude is giving me more value for same money.
If Claude is working for you then stick with it! Happy you’re getting good value from Claude.
At least with OpenAI you can use a third party harness like Pi.
Codex is fabulous at work, where token use is near limitless and ultra-thorough tool use is welcome. Go ahead and fire off searches for look-alike terms on my 96-core cloud instance.
By contrast, Claude Code's bias to make assumptions of reasonableness about underlying systems has proven to be immensely frustrating over the last month or two, both personally and at work. I've wasted days on "that was my mistake. I've been reporting numbers on the old architecture because I hadn't enabled the new one in the config" both at work and home. It's immensely frustrating.
But here we are. Wrestling with energetic idiots in model form, wrangled by over-specific harnesses that struggle to stay off of deranged side-quests.
What a time to be alive!
I had the opposite experience. Claude models and its harness feel like they are set to eat tokens for everything, especially if it’s ultracode effort. I have seen it spawn 6 agents and eat my 4-hour quota right in front of me. Codex is on point and follows instructions well even with max effort. I like my analogy of Claude being garrulous and Codex being laconic. If I see more limit hits in same sitting session, I have to rearrange my workflows. my experiments with qwen and deepseek have been good, cant wait to try glm and other models.
Just before I canceled my 20x Max sub I had a day where I had ~15% of my weekly I was trying to burn. I set it on ultracode and because I had set the max agents 32 for another project and forgot, the five research agents ended up spinning up a total of 26 subagents and burned through the remainder of my weekly in the span of 20 minutes before I noticed and shut it down.
“No, not like THAT!”
Claude did the same thing to me the other day. I ran out of my 5 hr limit, and it went into my $100 credit they had given me. Multiple parallel agents. It ate it in no time flat.
When I checked, all that credit was gone, I still wasn't into the next 5 hours, and all the agents had failed, returning nothing.
I didn't even get anything for burning all that credit. If I had paid for it, I'd be very, very pissed.
Similar experience here. I had raised my cap to $20 because they had given me promo credit. The credit expired without me using it and I didn’t notice.
One fine day I was like, oh my weekly quota resets soon, I will kick off an expensive bug hunt. It launched parallel things and burned $10 in like a moment.
It’s scary. I turned off extra usage after that.
How can you burn through your weekly budget in 20 minutes? You'd hit your 5 hour budget way before that, right?
The five hour budget is about 15% of the weekly on Max 20x. I had about 15% left.
Ah sorry, I read your earlier comment as you being at 15% of your weekly (so the prompt consuming 85%).
Here is an excerpt from the system prompt for UltraCode (Same for Fable,Opus,Sonnet):
"Ultracode. When a system-reminder confirms ultracode is on, that opt-in is standing: author and run a workflow for every substantive task by default. The goal is the most exhaustive, correct answer you can produce — token cost is not a constraint."
Requesting ultracode is basically asking for maximum token usage. If you want to limit consumption, use medium or high.
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same boat.
gpt 5.5/5.6 goes further on its own much more often than opus 4.8/5 does. codex capped ~300k context when claude does 1m.
I don't feel codex is saving tokens, and result is usually not as good imo.
> codex capped ~300k context when claude does 1m.
That's configurable in codex.. but there is a higher cost/usage to using it.
Are you kidding me? OpenAI weekly limits feel _infinite_. I run out of Anthropic limits reliably halfway through the week
You've articulated what I found unsettling about Boris' pov that "coding is a solved problem". I listened to a few of his talks and was instinctively off-put by that sentiment. I figured a fellow programmer would understand and speak on the nuances.
Granted it did make me think about my biases and to lean into more future facing inevitabilities. But you've nailed it, for Boris and Anthropic, they are betting that coding is a solved problem in the sense that any person can one-shot any random idea and the output will be in some abstract sense "good". And then at what cost and toward what end?
On the one hand it feels true. On the other I ask - what good software have anthropic, or anyone else, produced that was fully vibed?
As someone who does near 100% of my coding via LLM these days, i still find that for anything complex i am still looking at and thinking in terms of code. Im still quality checking and steering at some interval via code. And im still not sure how or whether i can replicate that level of thought without still dealing in code at times.
It's a scale thing. with one fairly simple Android app, it's doable. anything Enterprisey is a nightmare. maybe that's the lesson and the problem is not with the llms but with accidental complexity. Just right now I feel like I'm one mythical LLM minute away from the next clean pull request...
You'll have to define "good" before you can expect quality responses.
In this last week I've started reviewing code more and in just a short time, I've found 3 fairly simple things that were introduced by Claude that were not wrong per se, however, they were very inefficient and didn't address the root of the issue. I still think we're in a place where the output looks good as long as you don't look under the hood or keep it scoped to small, vibe-coded projects. Once you get beyond that it can fall apart. Anthropic must have a large codebase by now though. Yet I haven't seen much released from them about how they actually work day to day on development.
What makes you think Antropic has a large code base? what do they do exactly that would make them need a large code base? Or maybe the word Large can be understood in different way?
> who wins the long-term race
Isn’t the race between Chinese open-weight models and the others more decisive for the future?
it'll all be centralized models justifying their capability against local inference in, maybe 3 years or less
once we have a bit more memory fab capacity and the insane bottomless investment in AI giants realizes there is a bottom, local hardware will catch up with model performance to the extent that centralized inference will be downgraded to special cases or for orgs that find it cheaper than buying expensive hardware
but really most power users are going to have 1 TB unified RAM and local models that will do well enough
for light office use you can still have a cheap laptop and a claude subscription
I think the race is actually between locally optimized rigs with extremely strict context management, and the rest.
Those rigs are running one of the open Chinese models though, right?
> My money is on the more efficient solution. Even if Anthropic can win some benchmarks by using 3x tokens over 3x time, it is a terrible base to build toward the future. Users are no longer willing to wait exponentially long for linear improvements.
As much as I wish you were right, everything about software economics for the last 30+ years has favored _less efficient software_. Traditional hardware has been optimized for traditional software for decades and we still see bloated software win consistently. LLM hardware is at the start of its cycle, with abundant low-hanging fruit to conquer--I would expect the pro-bloat dynamics to weigh even more heavily in the LLM space than in the traditional software space.
LLMs are already of sufficient capability that if they were super cheap and fast and made no progress on intelligence, we will still make huge leaps in our ability to build systems and solve problems.
I'm just happy there is capital behind the efficiency path because I am confident we can get positive value on that path.
Oh no, I use the top shelf models every day and I really think they have a lot of room to improve in pretty much every regard. I suspect Fable usage is flatlining because it's not that good comparitively and way too expensive.
Seems like it wouldn't be hard for Anthropic to tweak a few prompts or RL pipelines to tune for terseness and token-efficiency if that stays as something that consumers want.
I find it unlikely that there's some fundamental property of OpenAI's models' "personality" or style which Anthropic (or any other serious AI firm) wouldn't be able to match if they wanted to.
They are both on borrowed time. The only thing keeping them afloat business wise is that current hardware costs are prohibitive which keeps local models artificially constrained. The next era will be open weight / local model for the masses and SOTA for the big players.
If your prognosis is true I'm not sure it's fully positive. Inference without batching is just massive less efficient, even if local hardware can be more energy efficient per operation and can skip out on cooling.
Open weights, obviously beneficial. Local compute when not necessary, seems like it'd be significantly worse for the environment?
To more fully flesh out what my thoughts on this:
I think because more devs cant run things locally, we are not getting the "open source gains" that you would get by having the network effect of more eyes on the work. Theres still little nuggets of gold in there though (eg antirez's DS4 project). But once more people can get their hands on hardware, I think the flood gates will open. And once that happens, I dont necessarily think people will run locally. But that will enable fungible service providers which we already see, but at a much larger scale.
To a lesser degree, open weights also leads to an eventuality of these two companies not being able to sustain their capital investments. Not to mention their pricing models are unsustainable as they currently stand. So they are being eroded from the outside-in, while also trying to fight the internal pressure to continue to raise prices/margins.
EDIT: I actually think the harness is more of a future for these big players. And theres real value in providing a high quality harness. So maybe they move to SAAS for claude code in the future. Who knows
Claude used to be 10x more efficient. I think there are no barriers of entry between one coding agent and the other. Therefore, I expect them to reverse as soon as people switch. At least this is what I will do.
If the problem isn't that hard, I've been using Cursor's Auto or Grok 4.5 (not 4.6, it's too slow).
They're both pretty damn competent and more important, Extremely Fast! I find the speed more useful than trying to be a hundred percent complete on every task. The big intelligent models screw up all the time as well, but I have to wait twenty minutes to three hours to find out.
GPT 5.6 is especially tenacious and seems to want to solve every bug in edge case 1000% all the time. Sometimes that's what you need, but a lot of times you're just trying to move fast and figure out what the product is.
There is no evidence regarding distillation. It is impossible to distill a model in just a month which was the gap between fable and Kimi k3. Anthropic wouldn't even keep up with the load. It is just another example of American exceptionalism.
Does Dario have the same relationship with the truth as Sam? (Their companies pirate books and develop products that compete at some level with those books’ authors, so obviously neither are that wonderfully trustworthy, so maybe “no evidence” meant you don’t believe this evidence rather than you weren’t aware of it. I would understand and respect your lack of belief!)
That's what any harness could do. By itself it's not evidence of distillation. Just mentioning Deepseek in there is just fear mongering, again American exceptionalism, which creates the belief only the US has the right to own cutting edge technology. It's a disservice to the entire world, and china happens to be the only challenger to that belief. They surely also asked for tasks to avoid mentioning Trump's involvement in the Epstein files and CP, but don't mention those, due to American exceptionalism. Dario has stated that he is an American exceptionalist. He powers Israeli/US bombings in Gaza, but only cares when China does the same.
This is evidence only if you're an American exceptionalist.
One can, say, hate America and feel its lunch is about to be munched by China and still read:
and think “oh, there’s alleged evidence of distillation“.The source is just anthropic saying what they believe and not providing any evidence beyond what they say. No raw chat logs to analyze independently. That's American exceptionalism
It’s not as trustworthy as it could be. Are you using the term as commonly known?
https://en.wikipedia.org/wiki/American_exceptionalism
Like, when I consider the Tuskegee Syphilis Experiments or MK Ultra, or Flock, I have bad things to say about them but American exceptionalism specifically wouldn’t cross my mind. Corporations anywhere playing a card close to the chest or even lying… superiority, exceptionalism, aren’t my top reference points.Since America is the first new nation, and individualism is a core value, the antithesis, communism, presents a direct threat. It's true that china can then be seen as a threat. My problem is with this bit: having a unique mission to transform the world. As we see with the pax silica agreement, even though it's not the stated mission of pax silica, the people behind it were born around that idea since a young age. No frontier US models is open source. Dario did not say in his open source letter, that his concerns about china also apply to the US, even though both countries are using ai in missiles today. I am just tired of this double standard where something is only bad if china or some other country does it like Singapore washing or the Panama papers even though it is standard corporate strategy worldwide to use legal domiciles in a country other than your own for fundraising or tax evasion. When Google does it, names are assigned like the Delaware loophole, but are spread far less than Singapore washing or the Panama papers
that seems like an american definition of american exceptionalism?
everyone else uses it as "Americans love to criticize everyone else, while pretending their farts dont stink"
Perhaps.
Perhaps partially covered in the “Critics of the concept say…”
Certainly weird to think the US isn’t chock full of problems (even if historically some stuff has been neat, like bringing together cultures and developing nifty tech in Silicon Valley).
When they do that they pay billions . Unlike China. That’s the order of law vs bunch of companies in a totalitarian government
They are not paying billions anymore. They just switched to buying and then destroying books. Arguably that's worse than training off of Anna's archive which Chinese companies still do. This comment is another example of American exceptionalism.
You know that buying a book vs buying a license is a very different purchase right ? And it does not work legally this way . Stop spreading made up stories
Can you really hold them responsible for book burning when they’re being compelled to do so by governmental laws? Seems like you should be pointing your finger at lawmakers, if anywhere.
You pay royalties to your publisher . They monitor situation , if a model has unfair amount of context about the book they bring you to court . Once they win they spread some money between owners + keep some money to fight future violations on the scale since it’s profitable for book publishers.
It’s economically lucrative for everyone in that chain to attack again and again ai vendors , unless they are in China . In this case they can only cry .
Me? A lowly commoner without hundreds of millions to lobby them? Why aren't American ai companies doing so? Too busy training models? They're shooting themselves in the foot when they could just use Anna's archive and lobbying is cheaper than paying billions in copyright settlements. Oh wait I am wrong. Shredding and scanning books is much cheaper than lobbying to use Anna's archive. Still can't do anything because I don't have money for lobbying
shouldn't you be pointing fingers at lawmakers and not to OP?
They paid $1.5 billions in July . Keep ignoring facts and believe in some nonsense
That was a one time payment. Another example of America exceptionalism assuming its a periodic payment like paying rent. look how they give money to publishers who then give back crumbs to the authors themselves.
Who told you it’s periodic ? To find a stolen book in llm is very easy . And if you break same rules twice any judge will fine you more for that .
That’s why in the western world you got book publishers . They have lawyers etc .If you prefer Chinese way : laugh at anyone who is taking about copyright , whether that a book , a model , or manufacturing secrets in eu , us or whatever sure .
A family business of my friend in eu was destroyed due to stealing until every single bolt position design of their system by China . They had no legal protection .
Keep calling rule of law vs no such rules an American exceptionalism .
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Looking like this will be the last month with Anthropic. Between the outages and just overall crap utility of Opus/Fable lately...
They'll all be getting around to this sooner or later, its just too expensive
I get incredible utility out of $200 per month
It's hard to put a number on it, but even accounting for all the time in meetings, talking with stakeholders and developers etc I'm over 10% more productive overall. I earn substantially more than $2000/month, the ROI is there
It's only expensive compared to the currently very strong offering from OpenAI. Or other models - my hobby projects are all on DeepSeek
What you’re saying is that they should be charging $2000 or more per month then.
Perhaps that’s true, but it’s a price tag that’s a lot harder to swallow for many orgs than $200/mo, and would require some hard justification for how your increased productivity contributes to the business bottom line.
I’ll agree that you can probably do that with hard numbers. I am skeptical that most $200/mo users could.
I think the rapid improvements in local models will make a $2,000/mo price point completely impossible to sustain. This feels like a race to the bottom.
yes and no, anthropic and openai are losing money on people who max out their sub, but openai has a lot more room to play with with much cheaper models to serve (by all signs we have from actual api/task pricing)
I posted on LinkedIn that I thought the future of AI will be local. I'm surprised I didn't get tarred and feathered, but it's been crickets.
I do believe it though. While the subsidies of the frontier providers are nice, they can't continue forever.
I believe it's been crickets because open-source/DIY solutions almost never become mainstream. Devs tend to think everyone wants a self-service to save a few bucks.
Most ordinary people don't care that much about privacy and if there is a solution that just works well enough to cover their needs and costs just fair enough to be affordable, they are going to use that. I feel like this is why fast food is such a thing. There are far better food options out there that either require a little bit more effort or money. Your post on Linkedin is akin to someone claiming in 1960's America that home-cooked burgers are the future, despite McDonalds gaining ground.
It is also why crypto wallets and the like never took off, people don't want to give up the convenience of a bank account, understandably.
That means people don't believe it. Same thing when people used to say personal computers would replace mainframes.
also codex + sol is really good and quite fast.
I switched when 4.7 dropped, after over a year on the service. It was an immediate improvement - not even 1 hour before Codex was giving me better results with less effort.
Stick with xhigh rather than turbo for most tasks though, now that the Age of Abundant Resets seems to be well and truly over for good (and 5h limits are supposedly returning soon).
Unfortunately Sol does not compare to Fable at all.
And Fable doesn't compare to Sol at all. Fable will block on many request in name of cybersecurity, sol never does that.
They're absolutely best in a chocolate-in-my-peanutbutter situation - I use them to adversarially review each other's changes and ping pong the branch back and forth - A makes changes, B reviews, B makes changes, A reviews. Together they're much smarter than either individually - anthropic models tend towards more creativity, openai models can get bogged down in the nitty gritty.
I'm getting to that point as well. Has anyone noticed that sometimes claude just seems way dumber on a random day? Like they're doing some internal tweaking? Also, I'm 100% convinced that it's verbose writing style is to generate tokens to make you hit your limit quicker. I have so many rules and it still talks in this bizarrely verbose, cryptic style where it's sometimes borderline impossible to understand what it's saying.
I haven’t had any issues with Fable or Opus code-wise, but the way it has started writing recently has almost become incomprehensible.
At the end of a long session it will start saying stuff like “There are smoke tests on the foundation-gates that are left for the cutting seam checks on these domains, which is genuinely your decision”
Never before the past couple months have I ever not been able to understand wtf it’s even saying lol
I'm seeing a lot of that too.
I was working on a project recently that required the attribution of a data source, and it added to the "licenses" page of the project something like "We use <blah> and per their terms we owe an acknowledgement of attribution to you, the user."
So in addition to the stuff it says in a session there's gobbledy gook that it prints out in copy as well.
The writing really is inscrutable at times.
Hahahaha I wasn’t sure if I was getting dumb or something. Mine finishes the tasks and then outputs paragraphs of that nonsense. But the code is great.
Same. especially Opus. It is unbearable.
My subscription expires tomorrow. Had subscribed ~March, eventually ended up paying for the $200 tier. However, there isn't enough of a moat for me to keep spending $200 if the models aren't being helpful anymore.
The unnecessarily jargon filled language was already pretty bad, but the latest Opus/Fable also just didn't seem to go far enough when asked to look into something, often leading me in circles.
Yeah it feels like they tune or 'optimize' the models after release and they get less useful to me as time goes by. I'm most productive the first few days after a release. Noticed this since opus 4.6.
Maybe with lower weekly quotas the load will be lower and we'll have fewer outages? A guy can dream.
I just cancelled my Max 5x plan. I was already mad at the limits, now Anthropic says it will get worse ? Nah, thanks.
For anyone on the fence, I was a hardcore CC user since it was released. I made the full switch to 5.6 sol and Codex about a month ago.
It's the better experience. The limits are way higher (I almost never burn through my $200/m plan), and the output is better than Opus 4.8 (Opus 5 is completely unusable for me).
I had a very similar experience. The combination of Claude going down frequently and the hype around open source models was enough for me to swap my harness from Claude Code to OpenCode. Then it became trivial to test out different models, and now the rest is history. Currently using OpenCode with z.ai and Codex $200/m plans for all my work atm.
You're underselling how good/reliable 5.6 sol is. It's in the fable discussion league not Opus4.8
I haven't used fable since they brought it back. But based on my experience before they removed it, I would agree that sol is pretty close.
Also try a hundred bucks on Openrouter and experiment with the Chinese models like Deepseek, Kimi, GLM. $100 will last a good while, and it isn't tied to a single model or provider.
I burned though $50 on OpenRouter in three days, this is with selective model routing based on tasks/strict AGENTS.md. A Claude 20x sub running Sonnet 5/Opus 5 and light Fable usage gets me through the month. It wasn't even close even though I wish it were.
Damn that's crazy. I put in $10 on the 5th of August and still have $1.99 left today, the 18th. I use Deepseek Flash almost exclusively.
Deepseek Flash is somewhere around the OpenAI Luna level though.
That's not bad (and nor is Luna!) but Opus/Sol are just massively better especially once you start doing agentic tasks.
See for example https://x.com/zainhas/status/2085567832268656755
Agreed, it's not SOTA but I'm happy with the trade off. My preference is to use mostly local models and augment them with Deepseek. It's been a pretty great equilibrium.
I have the $100 plan on OpenCode Zen, which I imagine is similar. I burn through it ridiculously fast. I haven't run the numbers, but it felt about the same as an Anthropic $20 plan
Yeah. Same. Deepseek Flash goes a long way, but it’s not capable enough for many tasks, so I end up defaulting to my Codex sub and just use Sol.
As a counter point, I've been using CC since December and I've never really had any problems with it. It's always done exactly what I want it to and I continue to be blown away by its capabilities, regardless of which of their models I've used. I also almost never burn through my $200/m plan.
Yep, switched from CC to 5.6 Sol. Not using it in my day job (only side projects), but I can crank 5.6 Sol on Extra High "fast mode" and never have to worry about credits.
Not doing crazy multi agent swarms, but have yet to hit any limits during pretty intense weekend sessions.
If you aren't using the full $200, you are losing money every month
What thought process gets you to that conclusion?
It's clearly not right if you compare it to API prices. It's even less right if you compare to a SWE salary.
Yes not using the full $200 means you aren't tokenmaxxing, but that seems about the most you can conclude from it.
I use Claude and Antigravity CLI as an (Arch) Linux desktop system administrator a lot lately. Is Codex useful for that too?
Not sure what Antigravity is, but Sol is good at sysadmin tasks.
The promotion is ending; the limits are reverting to pre-promotion levels.
"From May 13, 2026 through August 19, 2026, your weekly usage limit in Claude Code is 50% higher."
During this period however they’ve released models which lots of people report to be significantly more chatty. Framing it purely as a promotion ending feels like you’re giving them a bit too much credit. I doubt it’s a coincidence they started this promotion a week before the release of 4.8.
I think running a model unsupervised in anything above medium is a sucker move to burn more tokens. The high effort models can be great in limited context, but unsupervised they too often end up navel gazing. High doesn't always mean smarter, but it always burns more tokens. Medium and low seem to be decent for day to day tasks.
I am not sure the supervision is the problem, it's more the way Claude is acting in general, taking initiative that could burn thousands of token in a second. Just today I ask it a small fix on a newly pulled project, it wrote 5 lines of code but then immediately started to run the full test suites, which itself runs in docker, with several images that I didn't pull yet so it started to download everything and by the time I click stop, it already filled the context windows with dozen of hundreds of useless lines... I find it very hard to fins the sweet spot in the prompt between "do not assume, do not take initiatives" and "inform me if there is a simpler way to do what I am asking or if there are some downsides I may not have thought about".
> I think running a model unsupervised in anything above medium is a sucker move to burn more tokens.
What about errors compounding and any on-the-go decisions being made being the wrong ones? That kills anything long form, no matter how good and detailed your initial plan is - there will always be something along the way.
The models would need a way to identify a difficult problem and apply max reasoning there themselves and cruise through everything else at a lower level.
That’s my experience too, going off the deep end with CoT doesn’t meaningfully improve output on a lot of tasks but it does incinerate tokens and take longer
My favorite part (codex thing) is how it runs all commands twice, every time.
Once on a sandbox, realizes nothing works in its sandbox, then again outside the sandbox.
Fucking hell.
I add commands that constantly fall into this rabbit hole to AGENTS.md alongside an instruction for the agent to request escalation immediately instead of failing first then retrying out of the sandbox. It’s a hack, but it works.
I've already granted it permissions to do everything outside the sandbox.
It still starts off in the sandbox anyway. :/
I just run it in dangerous / yolo mode in my own sandbox. Works great and no more nagging.
I found the waffle reduced my overall usage. It doesn't matter much if it's smarter if it also needs more babysitting. It's quite good at making something quite advanced that is tangentially related to what you actually wanted.
As soon as it gets annoying enough to switch to another provider your Claude code tokens drop right off.
The model has a new improved tokenizer that also counts the same outputs as 20% more tokens
If they remove that extra 50%, I'm moving my $200 to Codex. Good thing we will know tomorrow, just a day before renewal.
"Your subscription will auto renew on Aug 20, 2026."
But I doubt they will remove it, just like they didn't remove Fable from the subscription. There's simply too much competition.
God I hope so, I'm rinsing my cc limits across two max accounts with ease atm
lol it already changed to Aug 31
Choco rations going up.
Double plus good, eh!
Anthropic has just announced extending the limits through August 31st with plans to make the new limits permanent.
https://xcancel.com/ClaudeDevs/status/2089798442306711646
I was just gonna blast them for the infinite promo extensions and Fable, but at least they apparently have noticed this indecisiveness problem themselves and making it permanent is definitely the best way to solve it, lol!
After they perma-extended Fable into including it into the max plan, I'm willing to give them the benefit of the doubt with this one.
I've been watching this to see if they "extend" it again, let it end, or make it permanent. I'm regularly hitting 90-100% on my $200/mo sub and will switch to Codex in a heartbeat if they drop these limits. This constant uncertainty is really annoying.
From their Twitter:
"We hope to make this a permanent change to our plans, but strong demand for our models means that capacity may be tight over the coming weeks. We’ll keep you posted as things develop."
https://xcancel.com/ClaudeDevs/status/2089798442306711646
Seeing how many people with Max accounts on Codex are complaining, your in for a rude awakening. The days that Codex was the undisputed usage king, seem to have been reversed. Its been most most noticed after they did like 20 resets in a month and half, ...
Exactly this. I don't think they are in a position to not extend it.
The link now says it's extended til August 31st.
Anthropic seems cooked right now in terms of compute
Flavor of the month LLM gets inundated and swamped with users.
Sideline LLMs have free compute and offer cheap prices to draw in crowd. Becomes flavor of the month LLM.
Back to step one.
It should be pretty clear by now that token prices are predominately a function of available compute.
To be fair, their growth is ridiculously insane. I don't know how else that can be described
They've been really struggling all of 2026. All of these "limited time" promos, just to have less usage than codex, and the shenanigans around "peak hour" reduction earlier in the year.
Their revenue has increased dramatically. The run rate was 9B in Dec, 19B in Mar, 47B in May. It's now at 65B.
https://www.bloomberg.com/news/articles/2026-08-17/anthropic...
Annualized. Which is another word for made-up.
Made up in the sense of "we estimate that revenue will not shring in the midterm".
Made up?
https://corporatefinanceinstitute.com/resources/accounting/r...
> As it extrapolates the current financial information and performance there is an implied assumption that the present financial environment will not change significantly in the future.
Yes, but their "run rate" assumes the current level continues unchanged, right? If revenue per month goes down then the projected run rate is optimistic. However, revenue has been increasing, so the reported run rates have underestimated revenue.
I think the better question is how much more than $65B/year revenue they need to cover what they are spending on capex and model development. I would bet money their revenue in the next year is over $75B (vs $65B), but also that their amortized costs exceed their revenue.
I think their capex will exceed their revenue, but $65B is a lot to spend on training runs!
I suspect it's more likely they will spend the extra money on hardware and infrastructure (data centers) either directly or via suppliers.
If you don't understand a concept, perhaps restrain yourself from commenting on it.
Meanwhile my $100/mo subscription allows me to spank Claude all day doing the work of 4 coders and never hit any limits.
This is my experience as well -- unless I'm using Fable. That one burns through tokens like a lightsaber through butter.
It’s like we’re hot-spotting, but across providers rather than across infrastructure!
Currently (and regularly) down, indeed.
it looks cooked to you, because growth numbers are cooking (to them)
(nobody uses claude anymore, it's too over-subscribed)
To anyone like me that switches between Codex and CC based on limits, but prefers CC to Codex, PI has been really great to migrate over. It can customize itself very easily, I was expecting to have to clone the repo or whatever, but no you can just tell it "add a manual mode where you present all changes as diffs in VSCode, letting me edit them or save to accept" and it will do it.
I wish I could use my Anthropic sub with it but I heard you get banned, but at least you can use it with any other subscription or model.
I got a max account during this promotion and it's been very fun but I'm a little burned out and am kind of looking forward to going back and tinkering with game engines without the help of an LLM for code gen (will still use it for documentation questions but I can do that with the free tier)
For fun/side stuff, handwritten code makes total sense, if you’re burnt out.
For anything that makes money, it feels like a huge step down in productivity, even with the downsides of agent-assisted code.
Oh yes I still use it at work.
The max account is for home projects where I'm basically making some common tools but tailored to myself (diet tracker, note app etc).
It's been great but across work and home it's just too much.
I too have the same experience with LLM generated code. I just get burnt out reading it and all the verbosity it has. I eventually gave up reading through it and keep it as a archive of previous work, while handwriting the code. If I get stuck somewhere, I asked the agent to generate a snippet based on my archived code and what i need to achieve and manually copy paste it.
I wish inline completions would have gotten better but it seems no effort is being put into it and it is frozen in time right now. Thankfully, the stuff i use this code for is simple and small scale. I can’t even begin to imagine how actual programmers are feeling about this.
That is about the time I started using Claude Code as a paid account at any level. Previously I was extremely skeptical. Overall, it works and it has sorted out some things I would have probably let go for a lot longer especially with the markup on my very ancient website. Markup issues, template migrations, maintaining stringent preservation going back to HTML that was hand crafted in the late 1990s. I also learned quickly you cannot ask the magic 8 ball to solve things. You have to make it read, and plan, and then review and go back and forth with it. This can legitimately take hours. The difference is I can oft get most of the website modernized rather than just some of it following the more traditional methods. I've also seen how one can hit those limits pretty quickly, if they are going down from here that will make it less useful. And no way I am paying more on a usage credit basis. Prior to this, all my code work had been strictly with local AI as the inference engine and I can go back to that.
Edit to add: As a 3 month experiment, it has been positive. I have gotten things to work that none of the people I have hired and paid over the years took care of. And I myself have been too busy to prioritize. It's a useful tool, but only a fool would think it replaces the judgment of a professional. Not yet anyway.
I forgot this was in effect. I’ve been hitting my weekly rate limits two to three days in because of needing to steer Slopus 5 with Fable. Absurd that they’re being cut further in the face of steep competition from open weights models.
On the same day that OpenAI cuts per token cost by 50% on GPT5.6 Sol. :')
This and the word watermarking is rubbing a lot of people the wrong way, me included.
Like, stop toying around with token limits and just focus on more efficient models.
Once the local models are good enough we are so abandoning these elephants.
I'm gonna walk as soon as possible.
They extended it: https://x.com/claudedevs/status/2089798442306711646
Someone here suggested they might keep it forever. Good to see they're considering it. Thanks!
prediction: extension of promotions because of the progressive move to codex.
With how bad Opus 5 and how expensive and limited Fable is, I would not be surprised.
Are there any figure to back up people moving to Codex?
I’ve been using both at the same time, but fable had me hitting my limits; even less will have me get 2x codex max instead of one of each.
I think the better comparison point is Opus 5. I'm also using both and I think overall I like Opus slightly better, but I'm still using Codex a lot for any project requiring image handling.
I moved a while back when Claude started refusing to do security audits and also failed to run properly in my sandbox without a lot of wrangling. Renamed Claude.md to agents.md and had no problems at all. There’s almost 0 switching cost.
No. Here's a data point: I tried it for a few days. While it worked fine I didn't see any benefit to switching since it costs the same ($100) and I've spent a year getting up to speed on Claude usage and quirks.
I for one, and I know of plenty others.
Will they, though? I could see Anthropic extending it since OpenAI cut the pricing of Sol by 50% for the time being.
Wasn't that a limited time promotion from OpenRouter? I didn't see anything from OpenAI themselves.
Sure seems like OAI is using their compute/capital advantage to dump. Seems improbable they're making a profit at those levels.
Why, it seems like the supply is limited by the ability to provide, and the demand is limited by market alienation.
They raise their prices too high, a lot of customers will still buy but be unhappy about it, it's burning goodwill for money. If they drop their prices too low they have overwhelming demand.
They could be making money hand over fist for all we know. We don't really know how much compute is being used, nor how much it cost them.
Only API or also sub?
Only on openrouter for some reason. Not OpenAI Subs/API.
A cautionary note. Your Claude account is tied to your email address, and it cannot be changed. If you lose access to your email address (I sold the domain), you cannot access your Claude account any more, you cannot change the email address, you can't cancel it, and the billing continues.
This happened to me, so far two months without any progress with Claude support trying to resolve it. Chatbot support got no response, email support got a single response after a month saying it had been passed on to another team to resolve. Mostly just silence.
I actually use claude these days mostly for mission critical tasks and code reviews. Everything else I use Sol. I have $20/month plans on both. For non-coding I also use Gemini on a $20/plan. So far I haven't had any issues but we'll see how things go. I have Qwen3.8-27B installed locally but until I upgrade my mac it's not for day to day stuff.
I’m supporting you as a company , but since grok 4.6 and codex , it’s just stupid to go with your pricing model . Cursor + grok + router that uses open ai and a bit of anthropic to verify tests etc it’s a no brainer .
Why should I pay you money , and have slower model and less intelligence? Oh yeah and I do not care about limits with cursor ultra at all . Unlike with you .
Cursor really is the best deal right now, the amount of usage you get with Grok is amazing and you can use frontier OpenAI or Anthropic models if you ever need to but most code can be written well by Grok.
It's not great if you don't want to use the Grok models though (and I don't, because it's now an Elon product), and if using Claude models via Cursor, the usage I get is way less, I was sometimes spending $60/month with Cursor and I get more with CC $18/month "Pro".
But CC took some getting used to, I also prefer the Cursor interface (the legacy "chat" pane).
Well yes, obviously it's not a good deal if you don't want to use its main product that they subsidize. If my grandmother had wheels she'd be a bike.
Have you used their CLI? I run everything in VMs or containers to prevent access to things on my host.
Everyone says that you hit token limits after some time using either Claude Code or its web version. Even though GPT 5.5 is cheaper and doesn't impose token limits, it's just too non-nuanced. The only points for which I still stick to using Claude are these:
- I actually rarely hit the token limits using my $20/mo web plan (switch chats when the current one feels "bloated" due to huge context and therefore the token drain), which even covers some of my coding sessions using Claude Code. - The visuals and "interactive" elements are still not introduced in GPT's web UI, unlike Claude's. - The nail in the coffin is the fact that Opus 4.8/5 is just BETTER at doing my RTL verification review jobs than GPT 5.5.
I am not glazing the model; it's just a personal preference for getting the job done...
I have no idea why anyone would spend the money Anthropic asks for Claude models these days. There was a brief window in time when it was worth the money to use them a bit through GitHub Copilot, but there's no way in hell I'm spending that for Claude Sonnet when DeepSeek is basically doing all of my work right now.
The charge me exactly the same: $100.
Claude Opus and Fable are so bad compared to GPT-5.6-Sol it's ridiculous, their desktop client is worse, and the value is worse because OpenAI has been spamming discounts. They better get their shit together at Anthropic!
Edit: If you're mad I'm light on the details I have provided some in the replies.
gpt-5.6-sol uses fewer tokens and OpenAI has been more generous with usage, but quality-wise I wouldn't say they are inferior to each other.
I have a Claude Code and OpenAI subscription so that I can use Opus/Fable/gpt-5.6 as I please, and the models are often catching things the other models missed. So much that I would significantly weaken my workflow if I dropped one subscription.
My best workflow at the moment is to create the initial plan with Fable (before review/revise-cycling with other models). From my own testing it seems slightly better at arriving at high-level ideal solutions after sweeping the whole project, projecting future needs, then coming up with good trade-offs like "by construction" correctness.
While mostly subjective, maybe the closest objectivity I have here is noticing fewer revision cycles needed with Fable-initialized plans.
Any model currently in 2026 is better than the ones of 2024. What is the quality difference really.
I mean i think if a developer has a good handle of the code the difference is marginal .
Unless we 100% offload the thinking to the model and act like a prompt manager. Maybe
For personal projects, I defer almost everything day-to-day to the models, so it gives me a good feel for what the models are good at.
Even then, it's kind of a wash these days between the sota models, and we're talking about maybe a 10% performance difference or something. But every once in a while there's the experience of one model spinning its wheels on a bug/repro/issue while another model comes in and one-shots the solution.
That make sense. Let me ask you this When the project reaches a level of complexity . Do you simply reach for better models or do you reengineer it or does the project scope stop at the egdge of the model's capabilities.
I am asking because in my personal projects after a while they becomes a giant messy ball of wires and i basically trust the model to untangle it for me , by the time it untangles properly, I run into my token limits.
With Opus 5 / Fable / gpt-5.6 you can simply ask them to fan out subagents to look for ideal architectural simplifications and rank their findings by impact vs confidence.
You can swap out "architectural simplification" with performance opportunities, bugs, correctness, etc. I get the orchestrator agent to then itemize it all into a file where I can keep track of which ones I've implemented.
The results are pretty astounding. I run these right before my weekly limits reset for each subscription and the findings will dictate the secondary tasks I get done during the week.
It's definitely token-heavy. I'm on the $200/mo Claude Code sub and the $100/mo Codex sub.
But it's pretty clear to me that software engineering is more or less solved and all you need is enough patience + tokens to get what you want. I think 20 years of engineering experience more lets me save on tokens rather than unlock things nobody else can build.
An example of the scope of one of my AI-engineered projects is a iterm2/ghostty-like terminal app that implements its own pty session, parsing, rendering. It's almost 2000 commits right now.
That said, I have a specific workflow that isn't just a blind "ok now make it so a screen can be split into panes". I have a plan phase focused on coming up with ideal invariants and such. But I'm not sure anymore how much of that is useful vs just yoloing a solution and then paying technical debt in sweeps, like garbage collection.
> software engineering is more or less solved
But the example you give is of a terminal for which there are copius examples in open source code. How hard is it really for a pattern matching machine to do that?
If I was doing it I would start by forking an existing repo and I might even say then that "software engineering is more or less solved since the open source revolution"
But I don't work on things like that.
Pretty much every software problem we work on breaks down into steps that are solved in prior art.
Even if it weren't, if you're capable of explaining the context and constraints of your problem, then a modern LLM with effort=high will generally come up with a solution that's worth starting with because it's well-reasoned.
Moreover, you can start with the solution and then course-correct based on future information because refactoring is trivial with an LLM, yet human projects often ratchet into a local optimum because refactoring is too expensive.
I don't think "it's been built before" does as much work as it seems. I didn't fork a project. The LLMs reasoned about how to build the project from scratch using trade-offs that made sense for my needs, and they made reasoned, unsolicited deviations from kitty, xterm, and co, not just blindly doing what some ref impl did. Btw, it was still a lot of work because my project isn't just "kitty but swift".
Then the models went on to drive a well-reasoned incremental implementation of a system that lets me use the terminal running on my Macbook from my iPhone over tailscale with a decent scheme it came up with itself.
The point is that I don't really have to know how things work to build good software with modern models. LLMs can do things like read Linux source code and adversarially refine ideas such that the final idea is a good one. And my biggest influences on the project can be automated through the use of reusable markdown files.
Now, I'm at risk of downplaying all my years in software here, but I see the writing on the wall. It was only one year ago that I only trusted AI to do autocomplete.
Every time I try to use a lower tier model like Terra or Sonnet I regret it, so I just use the best one the first time to keep my sanity (it sort of works). Same with effort, you gotta just max it out (though I stopped using Ultra/Ultracode) and I never use fast because I'd rather work in parallel on more than on one thing faster almost always.
In general, many of these stories of "one one shots it and the other spins on it" is down to trajectory divergence and can be achieved simply using another instance of the same model.
While just simply trying many times independently gets you the improvement that is due to pass@k vs 1, you can get huge improvements if on top of that, depending on your setting, you find a way to ensure some stochasticity by perturbing tool calls, etc and running multiple instances.
The general theme is, embrace the stochasticity rather than the leaky abstraction on top of it.
With modern LLMs, investing in this kind of harness tooling is much more fruitful than hoping for the best from the model.
While many basic instances of this are built in to the popular harnesses (much of cursors higher-than-usual success rate with older models was due to really excellent context mgmt), you can never beat one that is optimised for your particular codebase, infra and general setup.
Until last year or so, the context management needed varied too much at too coarse a level across different models and even model instances, but now they are all extremely robust in a much higher % of contexts and are thus way more amenable to developing context management tools for, without needing to do a research teams worth of evals.
Custom evals and harnesses are thus extremely high ROI now. We are finding companies needing to do less and less tweaks and getting much fewer regressions (you should have reg tests in ur evals) with every new usecase and every new model.
It can be really simple to start with: change your grep/rg that it uses to a script that does in effect "rg $@ | shuf".
More complex examples are: giving different subagents different tools, randomly failing tool calls, truncating file reads randomly, having a small model invent N possible failure modes causing a bug and appending that to N prompts and starting subagents from each - this all forces each to pursue different paths. $example_specific_to_your_company_setup is highest ROI though, since most companies actual failure modes are dominated by idiosyncratic API shapes and retrieval quirks that no usual harness will bother modelling.
Also important IMO to not assign any meaning or semantically interpret the CoT as an acceptance mechanism (it is ok to use it as a rejection mechanism e.g if you see it plotting a sandbox escape whether it eventually emits the exploit or not is not something you want to hedge). We have to resist the temptation and ensure we only interpret tool calls, codegen, etc in our evals and only think of the cot as "some output that pushes the conditional distribution" which may or may not semantically match the typical preceding tokens of the desired tool call.
Sure OpenAI has open source tools, and equivalent or better models, and lower prices, and they get along better with other agentic tools, but Anthropic has much better marketing and I guess that's what matters.
I don't know why this comment's getting down voted. It's absolutely true. I would also add that Anthropic seems to limit, compute, the more you use it because I'm on the Max subscription, and it just stops working for me.
I'll ask it to do something and it'll say, I tried, but I couldn't do it over and over again or some variation of.
But it doesn't do that at the start of my subscription, so...
> I don't know why this comment's getting down voted.
Because just calling something bad does not add a lot to the conversation. It's not thoughtful, interesting, or good.
The thing is, is it's not a subjective thing. It's objectively bad. I think that's what the story is or the appeal of the post. It's calling out, something that everyone else thinks is so great, but it's actually really pretty bad compared to the competition. Trust me, I used to want Claude to win, but it's not.
Huh? Comparing model quality is something everyone is constantly doing here. If you need more specifics, it speaks in an incomprehensible way, stops working lazily, does a bad job and misses things constantly, and makes a lot more mistakes. I have both a $200/mo Codex and Claude subscription and swap between them when one runs out, and I'm always more miserable when I have to use Claude.
The Claude desktop app is also widely panned, as I mentioned, and for me this mainly is due to general UX and a poor remote control interface. Codex's connected machine support is top notch.
I also mentioned the value of the Codex resets!
Because "$X is bad" is boring, especially when it comes to LLMs. I use Opus 5 and it's fine. It's more chatty and sometimes a little more difficult to steer than 4.x was, but I've found the code quality of 5 to be much higher.
Everyone has different experiences with these things (for example, I've never experienced what you describe), and "$X is bad" is not conducive to thoughtful discussion.
The issue isn't whether it's fine, it's that both Fable 5 and Opus 5 are worse to use for the job of programming than Codex-5.6-Sol in my experience. I am directly comparing these top tier models every week in my work, and many friends have left Claude in favor of Codex recently because of Claude's poor model quality.
One thing I do like about Claude is that the normal (non-Code) chat interface supports MCP, whereas ChatGPT basically does not.
It might be objectively true for you.
Opus 5 is fine for me and works better and faster on low and medium than higher effort on prior versions. Same as 5.6 Sol compared to 5.5 or 5.4.
This is just the cycle. If the OpenAI offerings are better and cheaper, people will shift there and then those discounts that made it such a deal will evaporate. Anthropic or someone else will entice people back with the discounts.
The whole thing is getting ridiculous.
I suspect the net result will be that more Pro $100 subscribers upgrade to $200/mo. If you explicitly do simpler stuff with Opus, you generally have enough Fable time for most programming and planning tasks.
Not to mention a lot of people who already have more than one max20 sub getting additional ones.
$100 Claude and $100 ChatGPT Pro is the best value for $200/month. They can see each others' mistakes.
The 'tokenmaxxing' and the extreme gambling fiesta with Anthropic's latest Claude Code slot machine engine called 'Fable 5' which has given many subsidies and free spins of the wheel and cheaper tokens are all incompatible with the desires of their future owner: Wall Street.
If Wall Street sees a single outage or a tiny drop in usage, they won't be happy and will pressure Anthropic to take away the free tokens.
Better to reduce the limits now rather than to wait until Wall St. tells them to just to avoid a stock punishment.
This is a very bad time for them to be doing this when other plans are being very liberal and catching up to Fable. I predict they will revert this decision once they see their sub numbers drop.
As we speak, Claude is down. I was already complaining about how extremely slow and dumb it has gotten since Opus 5. I guess this will be the last nail in the coffin for Claude. At least for me.
i'm using claude right now, like literally in an iterm2 window next to my browser window where I'm typing.
Might be regional.
https://status.claude.com/
I wonder if they schedule these promotions around training runs?
I saw this announcement when it came out and completely forgot about it. That explains why Claude Code felt so surprisingly generous these past few months.
So their only answer to DeepSeek V4, Kimi K3, GPT 5.6 price cuts on Luna (80%) and Sol (50% on OpenRouter) is to temporarily extend usage limits, then keep extending past the deadline every two weeks because they still don't have an answer. May through August, that's like 5 years in this industry and speaks volumes.
So your dealer has cut your drugs, isn't always available when he says he's going to be, and the price is going up?
The whole thing seems pretty opaque. I have a personal Pro subscription that I'm using exclusively with Claude Code on personal projects. I have no idea how close I'm currently getting to any limits, or whether that will start happening tomorrow. Nothing I've been able to find has really clarified it either way.
I've been using it on a few personal projects and run into the limits quite often. With Sonnet on high, I often hit right about the 5 hr mark when it resets. With Opus, I'll hit sooner.
I'm kind of surprised that you haven't been watching it with /usage to see where you're at. I've had a couple times that it ran out and lost what it was doing and had to start over, so I've gotten more careful.
And the time it burned $100 credit (that they gave us) and the fizzled with multiple agents, leaving me nothing of that work... Well, that was certainly instructive.
> I'm kind of surprised that you haven't been watching it with /usage to see where you're at.
TIL about the /usage command... Thanks!
And I suspect you're pushing Claude a lot harded than I am.
Then you'll probably also like /statusline too :D You just give it instructions on what you want to see down there, and it'll set it up. I like the model name and context.
I've never wanted to punch a meta physical entity in the face more, than I do Claude. I realised a lot of the AI context fatigue was from having to try and comprehend the absolute ridiculous wording. I cancelled my sub a while back (obviously).
So I upgraded to their Max 20x for nothing, then. Guess Kimi K3 and GLM 5.3 it is, then.
I have both chatGPT pro and Claude max accounts and I am considering switching Claude for Grok. Despite all those claude hypes, for me personally, claude just does not match codex in almost all tasks, both coding and non-coding.
I don't know, we've been the tiny hamsters in the biggest A/B test ever, I'm possibly very tired of the token/limits game. This is clearly not how this can be monetised (if that's even possible)
This might explain the outtages today, as folks race, misguidedly or not.-
Meanwhile every time their servers go down, your caches go down with it and you can pay for your entire context again. This sucks even harder when you like to use parallel subagents.
consumer hardware is moving towards local ai and the models you can run now locally are already at opus 4.6 level. within 3 years most pc's sold will be ai computers.
This is true for the next 6 months if that.
The future is models baked into directly into hardware, onto bare metal, serving 10k+ tokens/sec.
We can have our little models, they'll be serving a different customer.
The cost and knowledge required to do that is not viable for the average consumer. Same reason the whole OpenClaw thing imploded.
seems like just a month or so ago it was the new hotness [0]
[0] https://www.cnet.com/tech/services-and-software/from-clawdbo...
I wonder if this promotion was because of the summer holidays.
Does summer holidays only apply to Europeans? I think most Americans are still largely in office for August
People take much more time off during the summer in the USA than during other times of year. It’s somewhat regional, but it’s been true in all the place I have lived. Probably July is the most common month though because in some regions schools start sometime in August. It’s not uncommon for people to take 1-2w off during that period. More than 2w often requires extra approvals, so is less common.
Exactly. Say on average people take 2 weeks / 16 week off in that period, thats 12% traffic right there.
And smarter people than me can probably find some extra-linear relationship between usage and required limits for uptime etc.
Ah, forgot about that. I was questioning if I should switch my big subscription to ChatGPT (was on the 20$ Open AI and 100$ Claude), seems like a no brainer now
Buy a subscription, get something different every month.
Yeah, this is going to matter for me. Most of my sessions are long scoping/architecture conversations rather than coding loops.
"Note: We've extended this promotion. Increased weekly limits now run through August 31, 2026."
Yay, as expected.
Opus yesterday produced this gem: "Standing where it stood."
I replied, "never stop stopping!" and we had a stalemate, lol
And I think they started nerfing fable too, it wasn't able to merge some prs into main, fable!
they never made money on Claude code, it was always a way to get used recommend API access to your company
I thought this ended few weeks ago.
I have already moved away from anthropic for debugging and design in general and this will force me to look elsewhere for coding too
two claude max subs + one codex max here, just rotate to whichever isn't capped lol
Fix Opus.
And in the end, selling tokens ENCOURAGES the companies to sell more tokens. And how do they sell more tokens?
"Thinking" aka 'trust us bro!' without proof of thinking.
Making the model waste more tokens.
Advertisement: aka you pay to be advertised at.
Silently downgrading you and still faking models with the more costly tokens.
Intentional strategies to eat more tokens with no real gains.
Giving out almost-but-not-quite solutions that require another pull of the slo(t/p) machine.
oh wow, the new limits are basically unuseable
Was anyone impressed by Fable? I was never wowed by anything it generated.
Same here Fable has been thrash on my 5x Max, it's definitely been quantized, but not through API which is 10-20x as expensive.
So yeah, different people get different quality. I wouldn't be surprised if it calculates a wealth level, willingness to upgrade, influence, usage levels, etc. and decides what models to serve.
It's extremely obvious to me they've nerfed all models on my 5 Max from Fable to even 4.6, but i've tried through enterprise with huge differences in quality, and i've seen other people experiencing this both on reddit and twitter.
It's blowing my mind. Fable is the only AI model I use for coding, everything else is garbage for my use case.
I'm curious about your specific use case, if you're comfortable sharing it here.
Advanced mesh manipulation, shader writing and editing, 3D math, spatial awareness and analysis. It's not just better, it's the only model that straight up works (sorry for the claude speak). A league of its own.
Don't take my word for it, use a simple prompt of "create a shader showing [complex scene]" and see what the other models vomit out, including opus 4.6/4.8/5 and 5.6 sol (compare fable low effort with sol xhigh).
Vehicle physics/dynamics in my case and yes, same. I got a lot of mileage out of letting it use Opus/Sonnet sub agents for much of the exploratory and implementation work, which cuts down on token use. I got into way fewer "oh, that's nonsense? what about this then?" loops with Fable and it was the first model that actually tried to reason about the full system rather than fixating on details and chasing bits and pieces out of context. Haven't tried Sol yet but so far haven't had a reason to switch.
No need to switch as they give out free trials and Sol Is available on the 20$ plan. It's very fast for its power. I ask it for insight, read the responses myself, and offer its points back to Claude. More efficient than letting them talk to each other.
Tbh the extreme discrepancies between very confidently made statements about "X is better than Y" a sign a to me this is something where peoples' biases are out of control. Not saying you are wrong. Just that these things are so hard to evaluated apples to apples and that things like under-the-hood routing changes muddy the waters so much that it's really hard to get reasonable assessments.
My tests are very visual based and easy to notice when the seed/temp or the routing or the A/B test comes into play. And it's been months of working with these models so comparison is straightforward and robust. Fable is the first time I can use AI to code with good results while everyone has been doing it for ages before me.
If Anthropic doesn't figure out why OpenAI is eating their lunch, they're in some trouble. I'm guessing they already know why, but aren't able to accept that they won't somehow come out #1. Or in fact they really believe they will still come out #1. Delusion?
you guys are jumpy... relax
The "...aaaand it's gone" meme now applies to tokens and money at the same time. Clever AI future we live in!
Yet another scramble to use up weekly quota before an Anthropic cliff. This isn't fun.
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Will Anthropic be the Netscape or Yahoo of our time ?
This is ridiculous neither Netscape nor Yahoo made much money (source: I worked at Netscape). Anthropic is one of the largest fastest growing businesses of all time.
Quite a number of the smartest people I know got scalped to work at OpenAI. I don’t know anyone who went to Anthropic. Something I think which is under emphasized is that OpenAI has the human capital in addition to the financial capital advantage over Anthropic.
Over the long term I think OpenAI will produce the better experience when it comes to model quality, harness quality, and availability. I have been using codex the past few months and never looked back.