I've been testing it for several weeks. It can produce results that are truly epic, but it's still a case of rerolling the prompt a dozen times to get an image you can use. It's not God. It's definitely an enormous step though, and totally SOTA.
I work in Photoshop all day, and I 100% agree. Also, I just retried a task that wouldn't work last night on nano-banana and it worked first time on the released model, so I'm wondering if there were some changes to the released version?
We had an exhibition some time back where I used AI to generate the posters for our product. This is a side project and not something we do seriously, but the results were outstanding - better than what the majority of much bigger exhibitors had.
It took me a LOT of time to get things right, but if I was to get an actual studio to make those images, it would have cost me a thousands of dollars
Is it because the model is not good enough at following the prompt, or because the prompt is unclear?
Something similar has been the case with text models. People write vague instructions and are dissatisfied when the model does not correctly guess their intentions. With image models it's even harder for model to guess it right without enough details.
Remember in image editing, the source image itself is a huge part of the prompt, and that's often the source of the ambiguity. The model may clearly understand your prompt to change the color of a shirt, but struggle to understand the boundaries of the shirt. I was just struggling to use AI to edit an image where the model really wanted the hat in the image to be the hair of the person wearing it. My guess for that bias is that it had just been trained on more faces without hats than with them on.
It seems like every combination of "nano banana" is registered as a domain with their own unique UI for image generation... are these all middle actors playing credit arbitrage using a popular model name?
I'd assume they are just fake, take your money and use a different model under the hood. Because they already existed before the public release. I doubt that their backend rolled the dice on LMArena until nano-banana popped up. And that was the only way to use it until today.
Agreed, I didn't mean to imply that they were even attempting to run the actual nano banana, even through LMarena.
There is a whole spectrum of potential sketchiness to explore with these, since I see a few "sign in with Google" buttons that remind me of phishing landing pages.
Another nitpick - the pink puffer jacket that got edited into the picture is not the same as the one in the reference image - it's very similar but if I were to use this model for product placement, or cared about these sort of details, I'd definitely have issues with this.
I wonder how the creative workflow looks like when this kind of models are natively integrated into digital image tools. Imagine fine-grained controls on each layer and their composition with the semantic understanding on the full picture.
Regardless, it seems Google is on the frontier of every type of model and robotics (cars). It’s nutty how we forget what a intellectual juggernaut they are.
Before a model is announced, they use codenames on the arenas. If you look online, you can see people posting about new secret models and people trying to guess whose model it is.
Completely agree - I make logos for my github projects for fun, and the last time I tried SOTA image generation for logos, it was consistently ignoring instructions and not doing anything close to what i was asking for. Google's new release today did it near flawlessly, exactly how I wanted it, in a single prompt. A couple more prompts for tweaking (centering it, rotating it slightly) got it perfect. This is awesome.
I'd say it's more like comparing Sonnet 3.5 to Sonnet 4. GPT-4 was a rather fundamental improvement. It jumped to professional applications compared to the only causal use you could use ChatGPT 3.5 for.
I've tested it on Google AI Studio since it's available to me (which is just a few hours so take it with a grain of salt). The prompt comprehension is uncannily good.
My test is going to https://unsplash.com/s/photos/random and pick two random images, send them both and "integrate the subject from the second image into the first image" as the prompt. I think Gemini 2.5 is doing far better than ChatGPT (admittedly ChatGPT was the trailblazer on this path). FluxKontext seems unable to do that at all. Not sure if I were using it wrong, but it always only considers one image at a time for me.
Edit: Honestly it might not be the 'gpt4 moment." It's better at combining multiple images, but now I don't think it's better at understanding elaborated text prompt than ChatGPT.
I'm confused as well, I thought gpt-image could already do most of these things, but I guess the key difference is that gpt-image is not good for single point edits. In terms of "wow" factor it doesn't feel as big as gpt 3->4 though, since it sure _felt_ like models could already do this.
I've updated the GenAI Image comparison site (which focuses heavily on strict text-to-image prompt adherence) to reflect the new Google Gemini 2.5 Flash model (aka nano-banana).
This model gets 8 of the 12 prompts correct and easily comes within striking distance of the best-in-class models Imagen and gpt-image-1 and is a significant upgrade over the old Gemini Flash 2.0 model. The reigning champ, gpt-image-1, only manages to edge out Flash 2.5 on the maze and 9-pointed star.
What's honestly most astonishing to me is how long gpt-image-1 has remained at the top of the class - closing in on half a year which is basically a lifetime in this field. Though fair warning, gpt-image-1 is borderline useless as an "editor" since it almost always changes the whole image instead of doing localized inpainting-style edits like Kontext, Qwen, or Nano-Banana.
Why do Hunyuan, OpenAI 4o and Gwen get a pass for the octopus test? They don't cover "each tentacle", just some. And midjourney covers 9 of 8 arms with sock puppets.
Good point. I probably need to adjust the success pass ratios to be a bit stricter, especially as the models get better.
> midjourney covers 9 of 8 arms with sock puppets.
Midjourney is shown as a fail so I'm not sure what your point is. And those don't even look remotely close to sock puppets, they resemble stockings at best.
> Though fair warning, gpt-image-1 is borderline useless as an "editor" since it almost always changes the whole image instead of doing localized inpainting-style edits like Kontext, Qwen, or Nano-Banana.
Came into this thread looking for this post. It's a great way to compare prompt adherence across models. Have you considered adding editing capabilities in a similar way given the recent trend of inpainting-style prompting?
Adding a separate section for image editing capabilities is a great idea.
I've done some experimentation with Qwen and Kontext and been pretty impressed, but it would be nice to see some side by sides now that we have essentially three models that are capable of highly localized in-painting without affecting the rest of the image.
A bit mixed opinions - I tried colorizing manga pages with it, and the results were perfect.
Interestingly, it can change pages with tons of text on them without any problem, but cannot seem to do translation, if I ask it to translate a French comic page, the text ends up garbled (even though it can perfectly read and translate the text by itself).
I tried with another page, and it copypasted the same character (in different poses!) all over the panels. Absolutely uncanny!
However when I asked to remake a Western comic book in a manga style (provided a very similar manga page to the comic one), it totally failed.
Also about 50% of the time, it just tells me it'll generate the image but doesn't actually do it - not sure what's going on but a retry fixes it, but it's annoying.
I digitised our family photos but a lot of them were damaged (shifted colours, spills, fingerprints on film, spots) that are difficult to correct for so many images. I've been waiting for image gen to catch up enough to be able to repair them all in bulk without changing details, especially faces. This looks very good at restoring images without altering details or adding them where they are missing, so it might finally be time.
All of the defects you have listed can be automatically fixed by using a film scanner with ICE and a software that automatically performs the scan and the restoration like Vuescan. Feeding hundreds (thousands?) of photos to an experimental proprietary cloud AI that will give you back subpar compressed pictures with who knows how many strange artifacts seems unnecessary
I scanned everything into 48-bit RAW and treat those as the originals, including the IR scan for ICE and a lower quality scan of the metadata. The problem is sharing them - important images I manually repair and export as JPEG which is time consuming (15-30 minutes per image, there are about 14000 total) so if its "generic family gathering picture #8228" I would rather let AI repair it, assuming it doesn't butcher faces and other important details. Until then I made a script that exports the raws with basic cropping and colour correction but it can't fix the colours which is the biggest issue.
this reminds me of a joke we used to tell as kids when there was a new Photoshop version coming out - "this one will remove the cow from the picture and we'll finally see what great-grandpa looked like!"
Vuescan is terrible. SilverFast has better defaults. But nothing beats the orig Nikon scan software when using ICE. It does a great job of removing dust, fingerprints etc Even when you zoom in. VS what iSRD does in SilverFast, which if you zoom in and compare the 2. iSRD kinda smooches/blurs the infrared defects whereas Nikon Scan clones the surrounding parts, which usually looks very good when zooming in.
Both Silverfast and Nikon Scan methods look great when zoomed out.
I never tried Vuescan's infrared option. I just felt the positive colors it produced looks wrong/"dead".
I don't really understand the point of this usecase. Like, can't you also imagine what the photos might look like without the damage? Same with AI upscaling in phone cameras... if I want a hypothetical idea of what something in the distance might look like, I can just... imagine it?
I think we will eventually have AI based tools that are just doing what a skilled human user would do in Photoshop, via tool-use. This would make sense to me. But just having AI generate a new image with imagined details just seems like waste of time.
Do you happen to know some software to repair/improve video files? I'm in the process of digitalizing a couple of Video 2000 and VHS casettes of childhood memories of my mom who start suffering from dementia. I have a pretty streamlined setup for digitalizing the videos but I'd like to improve the quality a bit.
Topaz is probably the SOTA in video restoration, but it can definitely fuck shit up. Use carefully and sparingly and check all the output for weird AI glitches.
I tried a dozen or so images. For some it definitely failed (altering details, leaving damage behind, needing a second attempt to get a better result) but on others it did great. With a human in the loop approving the AI version or marking it for manual correction I think it would save a lot of time.
Sure, I could manually correct that quite easily and would do a better job, but that image is not important to us, it would just be nicer to have it than not.
I'll probably wait for the next version of this model before committing to doing it, but its exciting that we're almost there.
Being pragmatic, the after is a good restoration. There is nothing really lost (except some sharpness that could be put back). The main failing of AI is on faces because our brains are so hardwired to see any changes or weirdness. This is the sort of image that is perfect for AI because the subject's face is already occluded.
Another question/concern for me: if I restore an old picture of my Gramma, will my Gramma (or a Gramma that looks strikingly similar) ever pop up on other people's "give me a random Gramma" prompts?
I've been waiting for image gen to catch up enough to be able to repair them all in bulk without changing details, especially faces.
I've been waiting for that, too. But I'm also not interesting in feeding my entire extended family's visual history into Google for it to monetize. It's wrong for me to violate their privacy that way, and also creepy to me.
Am I correct to worry that any pictures I send into this system will be used for "training?" Is my concern overblown, or should I keep waiting for AI on local hardware to get better?
Are their models that have vector space that includes ideas, not just words/media but not entirely corporeal aspects?
So when generating a video of someone playing a keyboard the model would incorporate the idea of repeating groups of 8 tones, which is a fixed ideational aspect which might not be strongly represented in words adjacent to "piano".
It seems like models need help with knowing what should be static, or homomorphic, across or within images associated with the same word vectors and that words alone don't provide a strong enough basis [*1] for this.
*1 - it's so hard to find non-conflicting words, obviously I don't mean basis as in basis vectors, though there is some weak analogy.
Interesting! I feel like that's maybe similar to the business of being able to correctly generate images of text— it looks like the idea of a keyboard to a non-musician, but is immediately wrong to someone who is actually familiar with it at all.
I wonder if the bot is forced to generate something new— certainly for a prompt like that it would be acceptable to just pick the first result off a google image search and be like "there, there's your picture of a piano keyboard".
Anything that is heavily periodic can definitely trip up image gen - that being I just used Flux Kontext T2I and got a got pretty close (disregard the hammers though since thats a right mess). Only towards the upper register did it start to make mistakes.
I guess the vast majority of images have the palms the other way, that this biases the output. It's like how we misinterpret images to generate optical illusions, because we're expecting valid 3D structures (Escher's staircases, say).
I tried to reproduce the fork/spaghetti example and the fashion bubble example, and neither looks anything like what they present. The outputs are very consistent, too. I am copying/pasting the images out of the advertisement page so they may be lower resolution than the original inputs, but otherwise I'm using the same prompts and getting a wildly different result.
It does look like I'm using the new model, though. I'm getting image editing results that are well beyond what the old stuff was capable of.
The output consistency is interesting. I just went through half a dozen generations of my standard image model challenge, (to date I have yet to see a model that can render piano keyboard octaves correctly, and Gemini 2.5 Flash Image is no different in that regard), and as best I can tell, there are no changes at all between successive attempts: https://g.co/gemini/share/a0e1e264b5e9
This is in stark contrast to ChatGPT, where an edit prompt typically yields both requested and unrequested changes to the image; here it seems to be neither.
Flash 2.0 Image had the same issue: it does better than gpt-image for maintaining consistency in edits, but that also introduces a gap where sometimes it gets "locked in" on a particular reference image and will struggle to make changes to it.
In some cases you'll pass in multiple images + a prompt and get back something that's almost visually indistinguishable from just one of the images and nothing from the prompt.
Wildly different and subjectively less "presentable", to be clear. The fashion bubble just generates a vague bubble shape with the subject inside it instead of the"subject flying through the sky inside a bubble" presented on the site. The other case just adds the fork to the bowl of spaghetti. Both are reproducible.
Arguably they follow the prompt better than what Google is showing off, but at the same time look less impressive.
I am glad that I never decided to become a photoshop pro. I always contemplated about it, seemed attractive for a while, but glad that I decided against it. RIP r/photoshopbattles.
It was in the endless list of new shiny 'skills' that feels good to have. Now I can use nano-banana instead. Other models will soon follow, I am sure.
Retouching is an art. To the pro, this is just another tool to increase efficiency. You pay them not just for knowing how to use Photoshop, but for exercising good judgement. That said, I imagine this will shrink the field, since fewer retouchers will be able to do the same work, unless the amount of work goes up commensurately. Will people get more retouching done if the price goes down? Not sure.
Especially colouring, In college I worked for a dude who would re-colour old B&Ws for people, 60% the work (the work he enjoyed) was trying to research enough to know reasonably well what colour something actually ought to be, not just what we thought looked good.
Interesting take. I'm a programmer, but learned Photoshop in the early 2000s and had a blast making and editing images for fun. Sure, the generative models today can do a far better job than anything I could come up with, but that doesn't detract from the experience and skills I picked up over the years.
If anything, knowing Photoshop (I use Affinity Designer/Photo these days) is actually incredibly useful to finesse the output produced by AI. No regrets.
If you commented it a decade ago, I would say that at least you own the program and skills in case Google decides to turn off the lights or ask prohibitive price tag.
Now you need to pay subscription for PS and maybe there would be some decent open weight model released.
it's still a useful skill to know photoshop. AI images can be great but you are almost always going to want to A. create the base composition yourself B. clean up artifacts in the AI generation and C. layer AI compositions into a final work.
Programming and everything else will eventually fall to automation, too. It's just a matter of time.
Engineering probably takes a while (5 years? 10 years?) because errors multiply and technical debt stacks up.
In images, that's not so much of a big deal. You can re-roll. The context and consequences are small. In programs, bad code leads to an unmaintainable mess and you're stuck with it.
I'm unclear as to which side of the argument you're taking.
If you think that these tools don't automate most existing graphics design work, you're gravely mistaken.
The question is whether this increases the amount of work to be done because more people suddenly need these skills. I'm of the opinion that this does in fact increase demand. Suddenly your mom and pop plumbing business will want Hollywood level VFX for their ads, and that's just the start.
Half the time I ask Gemini to generate some image it claims it doesn't have the capability. And in general I've felt it's so hard to actually use the features Google announce? Like, a third of them is in one product, some in another which I can't use, and no idea what or where I should pay to get access. So confusing.
Yeah, in fact the website says "Try it in Gemini" and I'm not sure if I'm already trying it or not - if I choose Gemini 2.5 Flash in the regular Gemini UI, I'm using this?
It’s going to be a messy rollout as usual. The web app (gemini.google.com) shows “Images with Imagen” for me under tools for 2.5 flash but I just tried a few image edits and remixes in the iOS app and it looks like it’s been updated to this model.
Also very confused at this... It told me "I'm unable to create images of specific individuals in different settings." I wish it would at least say somewhere which model we are using at the moment.
I think not. Because at least in the aistudio there is a dedicated gemini-2.5-flash-image-preview model. So I am assuming it is not available in the standard gemini chat window.
I have to say while I'm deeply impressed by these text to image models, there's a part of me that's also wary of their impact. Just look at the comments beneath the average Facebook post.
I have been testing google's SynthID for images and while it isn't perfect, it is very good, insofar that I felt some relief from that same creeping dread over what these images will do to perceived reality.
It survives a lot of transformation like compression, cropping, and resizing. It even survives over alterations like color filtering and overpainting.
facebook isn't going to implement detection though. Many (if not most) of the viral pictures are AI-generated. and facebook is incentivized to let their users get fooled to generate endless scrolling
Along with those being fooled there are many comments saying this is fake, AI trash and etc. That portion of the commenters are teaching the ignorant and soon no one will believe what they see on the Internet as real.
I got scammed for $15k BTC last weekend during the (failed) SpaceX Launch. I believe the deepfake of Elon and transferred it over. The tech is very convincing, and the attacks ever increasingly sophisticated.
It was very convincing. We thought it was a YouTube stream of the Starship launch. It paused with 40 seconds remaining, and "Musk" came on offering to reward those who support innovation and technology (BTC, in this case). All info here: https://docs.google.com/document/d/1lRbApgKT4U95zN0AYsPQqsLR...
My problem with your statement isn't if its believable Elon came on stage or not, my problem is why would you trust Elon to pay you your money back, whether its the authentic or imposter Musk.
Kind of missing their point there. Giving Elon Musk $15k in crypto based on some vague too-good-to-be-true "trust me bro" pitch is embarrassing even if the video turned out to be real.
I got scammed similarly (although $10, because I tested first), because 1. it was on YouTube, on a channel called "SpaceX" with verified logo 2. with hundreds of thousands of viewers live 3. with a believable speech from Mr. Musk standing next to its rockets (and knowing his interest in cryptocurrencies).
This happened as I was genuinely searching for the actual live stream of SpaceX.
I am ashamed, even more so because I even posted the live stream link on Hacker News (!). Fortunately it was flagged early and I apologized personally to dang.
This was a terrible experience for me, on many levels. I never thought I would fall in such a trap, being very aware of the tech, reading about similar stories etc.
I am flabbergasted that you both get scammed. I would understand if this was two years ago, but now? Do people really not know about these scams? I can already see down votes coming for victim blaming, but this is to me really shocking. Notice that there isn't "tell hn: don't get scammed by deep fake crypto Elon" because people who usually posts also consider this general knowledge. That's why it's so effective I guess. In a similar manner there will never be "tell hn: don't drink acid it will burn your intestines", the danger is so obvious that nobody feels the need to post it and because nobody is posting it, people get scammed. I don't know what is the solution to that. How should you tell people what everybody should be already knowing?
I remember being on a machining workshop and he was telling such an obvious things. Obvious things are obvious until they aren't, and then somebody gets hurt.
Yes, I've heard about these scams. I've made deepfakes myself in the past. I've openly mocked people who have fallen for these scams. But this was sophisticated. Perfectly timed, very convincing deepfake, popular YouTube channels showing this stream during the launch, as if it were legit. The website was branded as SpaceX (the domain was obviously not, but I wasn't vigilant in the exciting hullabaloo of the impending launch). The instructions to participate were clear and easy to use.
Their bio mentions their actual job and one project that is verifiably real. I think that the elements that seem satirical are real projects they're working on.
I'm pretty sure the comment wasn't a joke? I saw the stream last week, it was very impressive use of AI, I didn't realize it was AI until he started talking about doubling crypto.
What about the bio is satirical? I'm pretty sure that's sincere too.
I didn't edit my bio. My projects are not satire. I'm just less ashamed than most, so I work on more "exciting" projects. I've worked extensively with generative AI, including video, myself. It was just that convincing to me in the moment. My regret knows no bounds. Luckily I earn enough this doesn't devastate me, but I really could have done some good with that money.
Please pardon me since I don't know if this is satirical or not. I'd wish if you could clarify it.
Because if this is real, then the world is cooked
if not, then the fact that I think that It might be real but the only reason I believe its a joke is because you are on hackernews so I think that either you are joking or the tech has gotten so convincing that even people on hackernews (which I hold to a fair standard) are getting scammed.
I have a lot of questions if true and I am sorry for your loss if that's true and this isn't satire but I'd love it if you could tell me if its a satirical joke or not.
Not satire. He made a big speech about rewarding those who invested early in tech to move humanity forward and the benefits of the blockchain. It was extremely convincing. Three college grads and a medical doctor were all convinced.
I guess it was something like [0] The Nigerian prince is now a deep fake Elon but the concept is the same. You need to send some money to get way more back.
I remember watching the SpaceX channel on youtube, which isn't a legit source. AI Elon basically says "I want to help make bitcoin more popular, let me show you how easy it it to transfer money around with btc. Send my $X and I'll send you back $2X! It's very inline with a typical elon message (I'll give you 1 million to vote R), it's on a channel called SpaceX. It's pretty believable.
Granted I played Runescape and EvE as a kid, so any double-isk scams are immediate redflags.
Even Elon could lose his credit card or something, the story they spin is always something like that "I am rich but in a pickle, please send some money here and then I'll send you back 10x as much tomorrow when I get back to my account", but of course they never send it back.
Edit: But of course Elon would call someone he knows rather than a stranger, rich people know a lot of people so of course they would never contact you about this.
There are a lot of people on the internet, and every individual on the internet is in a unique situation. Chances are some of them are very likely to be persuaded by a scam which seems obvious to you.
Parent’s story is very believable, even if parent made this particular story up (which I personally don‘t think is the case) this has probably happened to somebody.
These SpaceX scams are rampant on youtube and highly, highly lucrative. It’s crazy and you have to be very vigilant, as whatever is promised lines up with Elon’s MO.
Not to victim-shame or anything, but that sounds more like more than one safety mechanism failed, the convincing tech only being a rather small part of it?
Yes, more than one safety mechanism failed. Coinbase actually flagged the transaction, but I was so desperate to get it to go through, I went through their facial validation process to expedite the transaction. If I hadn't for just a couple more minutes, I'd have realized it was a scam.
I think the biggest failure is on the part of the companies hosting these streams.
Its been a while, but I remember seeing streams for Elon offering to "double your bitcoin" and the reasoning was he wanted to increase the adoption and load test the network. Just send some bitcoin to some address and he will send it back double!
But the thing was it was on youtube. Hosted on an imposter Tesla page. The stream had been going on for hours and had over ten thousand people watching live. If you searched "Elon Musk Bitcoin" During the stream on Google, Google actually pushed that video as the first result.
Say what you want about the victims of the scam, but I think it should be pretty easy for youtube or other streaming companies to have a simple rule to simply filter all live streams with Elon Musk + (Crypto|BTC|etc) in the title and be able to filter all youtube pages with "Tesla" "SpaceX" etc in the title.
I feel like somehow that would lessen it, but not really help much? There are obviously people with too much money in BTC who are trying to take any gamble to increase its value. It sounds like a deeper societal issue.
You are right that they might never be able to get it to 0, but shouldn't they lessen it if a simple measure like the one described can prevent a bunch of people from getting fooled by the scam?
If you believe anything the actual Elon says, then you have nobody to blame but yourself. That's not a sophisticated attack, you're just extremely gullible.
Come on, don't be mean. Imagine saying this in person to someone who just told you they got scammed. "You're just extremely gullible" is just so mean...show some empathy.
It's medium.com. YouTube comments quality text packaged as clickbait articles for some revenue share. It was always slop, even without LLMs. Do they even bother with paying human authors now or is the entire site just generated? That would probably be cheaper and improve quality.
> Do they even bother with paying human authors now
I thought Medium was a stuck up blogging platform. Other than for paid subscriptions, why would they pay bloggers? Are they trying to become the next HuffPost or something?
That lamp example is pretty impressive (though it's hard to know how cherry-picked it is). The lamp is plugged in, it's lighting the things in the scene, it's casting shadows.
I love that it's substantially faster than ChatGPT's image generation. It takes ages, so slow that the app tells you to not wait and sends you notification when the generation finishes.
How many images do you need? What are the use-cases that need a bunch of artificial yet photoreal images produced or altered without human supervision?
I think people still expect a lot of trial and error before getting a usable image. At 2 cents per pull of the slot machine lever, it would still take a while, though.
Strange. I was excited to play around with the 2.5 flash image after testing the nano banana in LMarena, but the results are not at all the same? So I went back to LMarena to replicate my earlier tests but it's way worse than when it was nano banana? Did I miss something?
I tried it, it gave a poor quality image that wasn't even what I asked for. I then asked for a correction, and it gave me another faulty image. Doesn't seem to be there
I don't get the hype. Tested it with the same prompts I used with Midjourney, and the results are worse than in Midjourney a year ago. What am I missing?
The hype is about image editing, not pure text-to-image. Upload an input image, say what you want changed, get the output. That's the idea. Much better preservation of characters and objects.
I tested it against Flux Pro Kontext (also image editing) and while it's a very different style and approach I overall like Flux better. More focus on image consistency, adjusts the lighting correctly, fixes contradictions in the image.
I've been testing it against Flux Pro Kontext for several weeks. I would say it beats Flux in a majority of tests, but Flux still surprises from time-to-time. Banana definitely isn't the best 100% of the time -- it falls a bit short of that. Evolution, not revolution.
Agreed. I find myself alternating between Qwen Image Edit 20B, Kontext, and now Flash 2.5 depending on the situation and style. And of course, Flash isn't open-weights, so if you need more control / less censorship then you're SOL.
Great question. I really doubt it would be able to support any resolution. I'm sure that behind the scenes it scales it down to somewhere around 1 mp before processing even if they decide to upscale and return it back at the original resolution.
I don't know. All the testing I've done has output the standard 1024x1024 that all these models are set to output. You might be able to alter the output params on the API or AI Studio.
Midjourney hasn't been SOTA for over a year. Even the latest release of version 7 scores extremely low on prompt adherence only managing to get 2 out of 12 prompts correct. Even Flux Dev running locally consistently out performs it.
Here's a comparison of Flux Dev, MJ, Imagen, and Flash 2.5.
That being said, if image fidelity is absolutely paramount and/or your prompts are relatively simple - Midjourney can still be fun to experiment with particularly if you crank up the weirdness / chaos parameters.
David Holz mentioned on Twitter that he was considering a Midjourney API. They're obviously providing it to Meta now, so it might become more broadly available after Midjourney becomes the default image gen for Meta products.
Midjourney wins on aesthetic for sure. Nothing else comes close. Midjourney images are just beautiful to behold.
David's ambition is to beat Google to building a world model you can play games in. He views the image and video business as a temporary intermediate to that end game.
It actually has impressive image generating ability, IMO. I think the two things go hand-in-hand. Its prompt adherence can be weaker than other models, though.
Anyone know how it handles '1920s nazi officer'? They stopped doing humans for a while but now I see they're back so I wonder how they're handling the criticism they got from that
"""
Unfortunately, I can't generate images of people. My purpose is to be helpful and harmless, and creating realistic images of humans can be misused in ways that are harmful. This is a safety policy that helps prevent the generation of deepfakes, non-consensual imagery, and other problematic content.
If you'd like to try a different image prompt, I can help you create images of a wide range of other subjects, such as animals, landscapes, objects, or abstract concepts.
"""
It's unfortunate they can't just explain the real reason they don't want to generate the image:
"Unfortunately I'm not able to generate images that might cause bad PR for Alphabet(tm) or subsidiaries. Is there anything else I can generate for you?"
The rejection message doesn’t seem to be accurate. I tried “happy person” as a prompt in AI Studio and it generated a happy human without any complaints.
It’s possible that they relaxed the safety filtering to allow humans but forgot to update the error message.
These models still seem to struggle with getting repeated patterns right. Others have mentioned piano keys; I've noticed they also almost always fail to generate a valid Go board.
I've had a task in mind for a while now that I've wanted to do with this latest crop of very capable instruction-following image editors.
Without going into detail, basically the task boils down to, "generate exactly image 1, but replace object A with the object depicted in image 2."
Where image 2 is some front-facing generic version, ideally I want the model to place this object perfectly in the scene, replacing the existing object, that I have identified ideally exactly by being able to specify its position, but otherwise by just being able to describe very well what to do.
For models that can't accept multiple images, I've tried a variation where I put a blue box around the object that I want to replace, and paste the object that I want it to put there at the bottom of the image on its own.
I've tried some older models, and ChatGPT, also qwen-image last week, and just now, this one. They all fail at it. To be fair, this model got pretty damn close, it replaced the wrong object in the scene, but it was close to the right position, and the object was perfectly oriented and lit. But it was wrong. (Using the bounding box method.. it should have been able to identify exactly what I wanted to do. Instead it removed the bounding box and replaced a different object in a different but close-by position.)
Are there any models that have been specifically trained to be able to infill or replace specific locations in an image with reference to an example image? Or is this just like a really esoteric task?
So far all the in-filling models I've found are only based on text inputs.
Not sure what your exact task is, but I have a similar goal as well. Haven't had time to try alot of different models or ideas yet because got busy with other stuff, but have you tried this: https://youtu.be/dQ-4LASopoM?si=e33FQd5f4fYr4J5L&t=299
where you stitch two images together, one is the working image (the one you want to modify), and the other one is the reference image, you then instruct the model what to do. I'm guessing this approach is as brittle as the other attempts you've tried so far, but I thought this seemed like an interesting approach.
Yes! There is a model called ACE++ from Alibaba that is specifically trained to replace masked areas with a reference image. We use it in https://phind.design. It does seem like a very esoteric and uncommon task though.
Not sure. If the Flash image output is $30/M [1] then that's pretty similar to gpt-image-1 costs. So a faster and better model perhaps but not really cheaper?
Since I can't edit, it seems like Flash image is about 23% (4 cents vs 17 cents) of the cost of Openai gpt-image-1, if you're putting an image and prompt in and getting out, say, a 1024x1024 generated image. With the quicker production time that makes it interesting. Expecting Openai to respond at least in terms of pricing, e.g. a flat rate output cap price or something to be comparable.
Never thought I would ever see this on a google owned websites!
Really? Google used to be famous not only for its errors, but for its creative error pages. I used to have a google.com bookmark that would send an animated 418.
Are men not attractive? Or perhaps for Google, this blog is a targeted content? But who is it targeting? I would like to see the reasoning behind using all women images (at the least the top/first ones) to show off the model capabilities. I have noticed this trend in the image manipulation business a lot.
The average man finds the average woman more attractive than the average woman finds the average man. Replace attractive with (eye-catching/attention-grabbing/motivating/retention-boosting).
Oh, in that case, it makes sense. Also, I think men/women consume different kind of media and this is one of those "men dominated" corner of the internet. I also think due to trainig data bias - there could be some difference in quality with different subjects. So, they might be showing off their best of best.
Because tech is largely male dominated and has inherent sexism/patriarchy and images of women, especially conventionally attractive ones, has the perception of aiding sales.
Also women are seen as more cooperative and submissive, hence so many home assistants and AI being women's voices/femme coded.
Thank you for saying that. When I posted that GP comment - it got immediately downvoted and I couldn't even see my comment on the thread. I kind of expected to get it tagged 'meta/off-topic' and removed.
The way I see it - corporations would like to exploit prejudices for revenue. Of course, this is not something new. But it is a societal issue and the corporate world is playing a large role in it.
This model is very impressive. Yesterday (as nano-banana) I gave it a photo of an indoor scene with a picture hanging on a wall, and asked it the picture on a wall with a copy of the whole photo. It worked perfectly the first time.
It didn't succeed in doing the same recursively, but it's still clearly a huge advance in image models.
this is amazing. I just wish models would have more non-textual controls. I don't want to TYPE my instructions. We need a better UI for editing images with AI.
I naively went onto Gemini in order to try to use the new model and had what I could only describe as the worst conversation I've had with an AI since GPT 3.5[1]. Is this really the model that's on top of the leaderboard right now? This feels about 500 ELO points worse than my typical conversation with GPT 5.
Edit: OK, OK, I actually got it to work, and yes, I admit the results are incredible[2]. I honestly have no idea what happened with Pro 2.5 the first time.
sometimes these bots just go awry. i wish you could checkpoint spots in a conversation so you could replay from a that point, maybe with a push in the latent space or a new seed.
I have a certain use case for such image generators. Feed them an entire news article I fetch from bbc and ask it to create an image to accompany the article. Thus far only midjourney managed to understand context. And now this, which is even more impressive. We live in interesting times.
I was able to upload my kids' back-to-school photos and ask nano-banana to turn them into a goth, an '80s workout girl, and a tracksuit mafioso. The results were incredibly believable, and I was able to prank my mom with them!
Imagen is a diffusion text to image model. You write some text that describes your image, you get an image out and that's it.
Flash Image is an image (and text) predicting large language model. In a similar fashion to how trained LLMs can manipulate/morph text, this can do that for images as well. Things like style transfer, character consistency etc.
You can communicate with it in a way you can't for imagen, and it has a better overall world understanding.
Seems to be failing at API Calls right now with "You exceeded your current quota, please check your plan and billing details. For more information on this error,"
In EU they forbid us newspapers from non-approved countries, impose cookies banners everywhere, and now block porn. Soon they will forbid some AI models which have not passed EU censorship ("safety") validation. Because we all know that governments (or even Google with Android) are better at knowing what is the safest for you.
All these image models are time vampires and need to be looked at with very suspicious eyes. Try to make a room - that's easy, now try to make multiple views of the same room - next to impossible. If one is intending to use these image models for anything that requires consistency of imagery, forget it.
These jobs won't go away. Power tools didn't destroy carpentry. Computers didn't destroy math. But workers who don't embrace these new tools will probably get left behind by those who do.
I'm really waiting for a Pro sized Gemini model with image output.
I experimented heavily with 2.0 for a site I work on, but it never left preview and it had some gaps that were clearly due to being a small model (like lacking world knowledge, struggling with repetition, missing nuance in instructions, etc.)
2.5 Flash/nano-banana is a major step up but still has small model gaps peeking through. It still gets to "locked in" states where it's just repeating itself, which is a similar failure mode of small models for creative writing tasks.
A 2.5 Pro would likely close those gaps and definitively beat gpt-image-1
AI is supposed to set us all free. Yet, so far all the tech companies have done is eliminate the jobs of the lowest-paid people (artists, writers, photographers, designers) and transfer that money to billionaires. Yay.
[Plows] are supposed to set us all free. Yet, so far all the tech companies have done is eliminate the jobs of the lowest-paid people ([field hands]) and transfer that money to landowners. Yay.
An image seems to be 256 tokens looking the AIstudio tab, so you can generate 3906,25 images per 1M tokens, that seems a lot if I'm not wrong in some ways.
Edit: the blog post is now loading and reports "1290 output tokens per image" even though on the AI studio it said something different.
Still fails the “full glass of wine” test, and still shows many of the artifacts typical of AI generated images like non-nonsensical text, misplacement of objects, etc.
To be honest I am kind of glad. As AI generated images proliferate, I am hoping it will be easier for humans to call them out as AI.
This is the gpt 4 moment for image editing models. Nano banana aka gemini 2.5 flash is insanely good. It made a 171 elo point jump in lmarena!
Just search nano banana on Twitter to see the crazy results. An example. https://x.com/D_studioproject/status/1958019251178267111
I've been testing it for several weeks. It can produce results that are truly epic, but it's still a case of rerolling the prompt a dozen times to get an image you can use. It's not God. It's definitely an enormous step though, and totally SOTA.
If you compare to the amount of effort required in Photoshop to achieve the same results, still a vast improvement
I work in Photoshop all day, and I 100% agree. Also, I just retried a task that wouldn't work last night on nano-banana and it worked first time on the released model, so I'm wondering if there were some changes to the released version?
We had an exhibition some time back where I used AI to generate the posters for our product. This is a side project and not something we do seriously, but the results were outstanding - better than what the majority of much bigger exhibitors had.
It took me a LOT of time to get things right, but if I was to get an actual studio to make those images, it would have cost me a thousands of dollars
Vibe coding might not be real, but vibe graphics design certainly is.
https://imgur.com/a/internet-DWzJ26B
Anyone can make images and video now.
What tools did you use to make those videos from the PG image?
I used a bunch of models in conjunction:
- Midjourney (background)
- Qwen Image (restyle PG)
- Gemini 2.5 Flash (editing in PG)
- Gemini 2.5 Flash (adding YC logo)
- Kling Pro (animation)
I didn't spend too much time correcting mistakes.
I used a desktop model aggregation and canvas tool that I wrote [1] to iterate and structure the work. I'll be open sourcing it soon.
[1] https://getartcraft.com
Is it because the model is not good enough at following the prompt, or because the prompt is unclear?
Something similar has been the case with text models. People write vague instructions and are dissatisfied when the model does not correctly guess their intentions. With image models it's even harder for model to guess it right without enough details.
Remember in image editing, the source image itself is a huge part of the prompt, and that's often the source of the ambiguity. The model may clearly understand your prompt to change the color of a shirt, but struggle to understand the boundaries of the shirt. I was just struggling to use AI to edit an image where the model really wanted the hat in the image to be the hair of the person wearing it. My guess for that bias is that it had just been trained on more faces without hats than with them on.
No, my prompts are very, very clear. It just won't follow them sometimes. Also this model seems to prefer shorter prompts, in my experience.
How did you get early access? Thanks.
No, it's not really that much of an improvement. Once you start coming up with specific tasks, it fails just like the others.
Alarming hands on the third one: it can't decide which way they're facing. But Gemini didn't introduce that, it's there in the base image.
Yes, the base image's hands are creepy.
It seems like every combination of "nano banana" is registered as a domain with their own unique UI for image generation... are these all middle actors playing credit arbitrage using a popular model name?
I'd assume they are just fake, take your money and use a different model under the hood. Because they already existed before the public release. I doubt that their backend rolled the dice on LMArena until nano-banana popped up. And that was the only way to use it until today.
Agreed, I didn't mean to imply that they were even attempting to run the actual nano banana, even through LMarena.
There is a whole spectrum of potential sketchiness to explore with these, since I see a few "sign in with Google" buttons that remind me of phishing landing pages.
They're almost all scams. Nano banana AI image generator sites were showing up when this model was still only available in LM Arena.
Another nitpick - the pink puffer jacket that got edited into the picture is not the same as the one in the reference image - it's very similar but if I were to use this model for product placement, or cared about these sort of details, I'd definitely have issues with this.
I wonder how the creative workflow looks like when this kind of models are natively integrated into digital image tools. Imagine fine-grained controls on each layer and their composition with the semantic understanding on the full picture.
Regardless, it seems Google is on the frontier of every type of model and robotics (cars). It’s nutty how we forget what a intellectual juggernaut they are.
Tool use and sycophancy are still big issues in gemini 2.5 models.
Why is it called nano banana?
Before a model is announced, they use codenames on the arenas. If you look online, you can see people posting about new secret models and people trying to guess whose model it is.
What are "the arenas"?
Blind rating battlegrounds, one is https://lmarena.ai/ (first google result)
Engineers often have silly project names internally, then some marketing team rewrites the name for public release.
I'm pretty sure it's because an image of a banana under a microscope generated by the model went super viral
Or was that just marketing?
Oh no, even more mis-scaled product images.
Completely agree - I make logos for my github projects for fun, and the last time I tried SOTA image generation for logos, it was consistently ignoring instructions and not doing anything close to what i was asking for. Google's new release today did it near flawlessly, exactly how I wanted it, in a single prompt. A couple more prompts for tweaking (centering it, rotating it slightly) got it perfect. This is awesome.
cope
> This is the gpt 4 moment for image editing models.
No it's not.
We've had rich editing capabilities since gpt-image-1, this is just faster and looks better than the (endearingly? called) "piss filter".
Flux Kontext, SeedEdit, and Qwen Edit are all also image editing models that are robustly capable. Qwen Edit especially.
Flux Kontext and Qwen are also possible to fine tune and run locally.
Qwen (and its video gen sister Wan) are also Apache licensed. It's hard not to cheer Alibaba on given how open they are compared to their competitors.
We've left the days of Dall-E, Stable Diffusion, and Midjourney of "prompt-only" text to image generation.
It's also looking like tools like ComfyUI are less and less necessary as those capabilities are moving into the model layer itself.
In other words, this is the gpt 4 moment for image editing models.
Gpt4 isn't "fundamentally different" from gpt3.5. It's just better. That's the exact point the parent commenter was trying to make.
I'd say it's more like comparing Sonnet 3.5 to Sonnet 4. GPT-4 was a rather fundamental improvement. It jumped to professional applications compared to the only causal use you could use ChatGPT 3.5 for.
did you see the generated pic demis posted on X? it looks like slop from 2 years ago. https://x.com/demishassabis/status/1960355658059891018
I've tested it on Google AI Studio since it's available to me (which is just a few hours so take it with a grain of salt). The prompt comprehension is uncannily good.
My test is going to https://unsplash.com/s/photos/random and pick two random images, send them both and "integrate the subject from the second image into the first image" as the prompt. I think Gemini 2.5 is doing far better than ChatGPT (admittedly ChatGPT was the trailblazer on this path). FluxKontext seems unable to do that at all. Not sure if I were using it wrong, but it always only considers one image at a time for me.
Edit: Honestly it might not be the 'gpt4 moment." It's better at combining multiple images, but now I don't think it's better at understanding elaborated text prompt than ChatGPT.
I'm sorry I absolutely don't agree. This model is on a whole other level.
It's not even close. https://twitter.com/fareszr/status/1960436757822103721
I'm confused as well, I thought gpt-image could already do most of these things, but I guess the key difference is that gpt-image is not good for single point edits. In terms of "wow" factor it doesn't feel as big as gpt 3->4 though, since it sure _felt_ like models could already do this.
People really slept on gpt-image-1 and were too busy making Miyazaki/Ghibli images.
I feel like most of the people on HN are paying attention to LLMs and missing out on all the crazy stuff happening with images and videos.
LLMs might be a bubble, but images and video are not. We're going to have entire world simulation in a few years.
I've updated the GenAI Image comparison site (which focuses heavily on strict text-to-image prompt adherence) to reflect the new Google Gemini 2.5 Flash model (aka nano-banana).
https://genai-showdown.specr.net
This model gets 8 of the 12 prompts correct and easily comes within striking distance of the best-in-class models Imagen and gpt-image-1 and is a significant upgrade over the old Gemini Flash 2.0 model. The reigning champ, gpt-image-1, only manages to edge out Flash 2.5 on the maze and 9-pointed star.
What's honestly most astonishing to me is how long gpt-image-1 has remained at the top of the class - closing in on half a year which is basically a lifetime in this field. Though fair warning, gpt-image-1 is borderline useless as an "editor" since it almost always changes the whole image instead of doing localized inpainting-style edits like Kontext, Qwen, or Nano-Banana.
Comparison of gpt-image-1, flash, and imagen.
https://genai-showdown.specr.net?models=OPENAI_4O%2CIMAGEN_4...
Why do Hunyuan, OpenAI 4o and Gwen get a pass for the octopus test? They don't cover "each tentacle", just some. And midjourney covers 9 of 8 arms with sock puppets.
Good point. I probably need to adjust the success pass ratios to be a bit stricter, especially as the models get better.
> midjourney covers 9 of 8 arms with sock puppets.
Midjourney is shown as a fail so I'm not sure what your point is. And those don't even look remotely close to sock puppets, they resemble stockings at best.
> Though fair warning, gpt-image-1 is borderline useless as an "editor" since it almost always changes the whole image instead of doing localized inpainting-style edits like Kontext, Qwen, or Nano-Banana.
Came into this thread looking for this post. It's a great way to compare prompt adherence across models. Have you considered adding editing capabilities in a similar way given the recent trend of inpainting-style prompting?
Adding a separate section for image editing capabilities is a great idea.
I've done some experimentation with Qwen and Kontext and been pretty impressed, but it would be nice to see some side by sides now that we have essentially three models that are capable of highly localized in-painting without affecting the rest of the image.
https://mordenstar.com/blog/edits-with-kontext
You need a separate benchmark for editing of course
A bit mixed opinions - I tried colorizing manga pages with it, and the results were perfect.
Interestingly, it can change pages with tons of text on them without any problem, but cannot seem to do translation, if I ask it to translate a French comic page, the text ends up garbled (even though it can perfectly read and translate the text by itself).
I tried with another page, and it copypasted the same character (in different poses!) all over the panels. Absolutely uncanny!
However when I asked to remake a Western comic book in a manga style (provided a very similar manga page to the comic one), it totally failed.
Also about 50% of the time, it just tells me it'll generate the image but doesn't actually do it - not sure what's going on but a retry fixes it, but it's annoying.
I digitised our family photos but a lot of them were damaged (shifted colours, spills, fingerprints on film, spots) that are difficult to correct for so many images. I've been waiting for image gen to catch up enough to be able to repair them all in bulk without changing details, especially faces. This looks very good at restoring images without altering details or adding them where they are missing, so it might finally be time.
All of the defects you have listed can be automatically fixed by using a film scanner with ICE and a software that automatically performs the scan and the restoration like Vuescan. Feeding hundreds (thousands?) of photos to an experimental proprietary cloud AI that will give you back subpar compressed pictures with who knows how many strange artifacts seems unnecessary
I scanned everything into 48-bit RAW and treat those as the originals, including the IR scan for ICE and a lower quality scan of the metadata. The problem is sharing them - important images I manually repair and export as JPEG which is time consuming (15-30 minutes per image, there are about 14000 total) so if its "generic family gathering picture #8228" I would rather let AI repair it, assuming it doesn't butcher faces and other important details. Until then I made a script that exports the raws with basic cropping and colour correction but it can't fix the colours which is the biggest issue.
How did you get the 49bit and ICE data separately? Did you double scan everything?
I'm scanning my parents photos at the moment.
this reminds me of a joke we used to tell as kids when there was a new Photoshop version coming out - "this one will remove the cow from the picture and we'll finally see what great-grandpa looked like!"
Vuescan is terrible. SilverFast has better defaults. But nothing beats the orig Nikon scan software when using ICE. It does a great job of removing dust, fingerprints etc Even when you zoom in. VS what iSRD does in SilverFast, which if you zoom in and compare the 2. iSRD kinda smooches/blurs the infrared defects whereas Nikon Scan clones the surrounding parts, which usually looks very good when zooming in.
Both Silverfast and Nikon Scan methods look great when zoomed out. I never tried Vuescan's infrared option. I just felt the positive colors it produced looks wrong/"dead".
I don't really understand the point of this usecase. Like, can't you also imagine what the photos might look like without the damage? Same with AI upscaling in phone cameras... if I want a hypothetical idea of what something in the distance might look like, I can just... imagine it?
I think we will eventually have AI based tools that are just doing what a skilled human user would do in Photoshop, via tool-use. This would make sense to me. But just having AI generate a new image with imagined details just seems like waste of time.
Not everyone has a great imagination.
Read up on aphantasia.
Do you happen to know some software to repair/improve video files? I'm in the process of digitalizing a couple of Video 2000 and VHS casettes of childhood memories of my mom who start suffering from dementia. I have a pretty streamlined setup for digitalizing the videos but I'd like to improve the quality a bit.
I've used products from topazlabs.com for the same problem and have generally been happy with them.
Topaz is probably the SOTA in video restoration, but it can definitely fuck shit up. Use carefully and sparingly and check all the output for weird AI glitches.
I didn't do any videos, just pictures, but considering how little I found for pictures I doubt you'll find much
VHSdecode if you want a rabbit hole.
Hope it works well for you!
In my eyes, one specific example they show (“Prompt: Restore photo”) deeply AI-ifies the woman’s face. Sure it’ll improve over time of course.
I tried a dozen or so images. For some it definitely failed (altering details, leaving damage behind, needing a second attempt to get a better result) but on others it did great. With a human in the loop approving the AI version or marking it for manual correction I think it would save a lot of time.
This is the first image I tried:
https://i.imgur.com/MXgthty.jpeg (before)
https://i.imgur.com/Y5lGcnx.png (after)
Sure, I could manually correct that quite easily and would do a better job, but that image is not important to us, it would just be nicer to have it than not.
I'll probably wait for the next version of this model before committing to doing it, but its exciting that we're almost there.
Being pragmatic, the after is a good restoration. There is nothing really lost (except some sharpness that could be put back). The main failing of AI is on faces because our brains are so hardwired to see any changes or weirdness. This is the sort of image that is perfect for AI because the subject's face is already occluded.
Another question/concern for me: if I restore an old picture of my Gramma, will my Gramma (or a Gramma that looks strikingly similar) ever pop up on other people's "give me a random Gramma" prompts?
That time had arrived a few months ago already with Flux Kontext (https://bfl.ai/models/flux-kontext).
I've been waiting for image gen to catch up enough to be able to repair them all in bulk without changing details, especially faces.
I've been waiting for that, too. But I'm also not interesting in feeding my entire extended family's visual history into Google for it to monetize. It's wrong for me to violate their privacy that way, and also creepy to me.
Am I correct to worry that any pictures I send into this system will be used for "training?" Is my concern overblown, or should I keep waiting for AI on local hardware to get better?
Like most image generators, it didn’t pass the piano keyboard test. (Black keys are wrong.)
https://aistudio.google.com/app/prompts?state=%7B%22ids%22:%...
What is the piano keyboard test? Your link requires granting AI Studio access to Google Drive, which I do not want to do.
Just ask it to generate a correct piano keyboard. It's something the current gen of image generator AIs fail at.
Do most humans pass?
Most humans fail at 4 digits multiplication, or drawing a cube in perspective.
Presumably most humans with a camera do
2-2-1-2-2-2-1
I still feel like most humans would fail, haha.
Are their models that have vector space that includes ideas, not just words/media but not entirely corporeal aspects?
So when generating a video of someone playing a keyboard the model would incorporate the idea of repeating groups of 8 tones, which is a fixed ideational aspect which might not be strongly represented in words adjacent to "piano".
It seems like models need help with knowing what should be static, or homomorphic, across or within images associated with the same word vectors and that words alone don't provide a strong enough basis [*1] for this.
*1 - it's so hard to find non-conflicting words, obviously I don't mean basis as in basis vectors, though there is some weak analogy.
How would you encode those ideas?
The selling point of this model really seems to be it's consistency between generations rather than it's raw generating ability.
for instance:
https://aistudio.google.com/app/prompts/1gTG-D92MyzSKaKUeBu2...
I can’t see it. You probably need to set permissions to “anyone with the link can access.”
Interesting! I feel like that's maybe similar to the business of being able to correctly generate images of text— it looks like the idea of a keyboard to a non-musician, but is immediately wrong to someone who is actually familiar with it at all.
I wonder if the bot is forced to generate something new— certainly for a prompt like that it would be acceptable to just pick the first result off a google image search and be like "there, there's your picture of a piano keyboard".
Anything that is heavily periodic can definitely trip up image gen - that being I just used Flux Kontext T2I and got a got pretty close (disregard the hammers though since thats a right mess). Only towards the upper register did it start to make mistakes.
https://imgur.com/a/fyX42my
or my "hands with palms facing down" test.... no matter how hard I try it just can't get open hands, palms down.
It's probably just a matter of rerolling a few times. I was able to get it around 25% of the time.
https://imgur.com/a/H9gH3Zy
I guess the vast majority of images have the palms the other way, that this biases the output. It's like how we misinterpret images to generate optical illusions, because we're expecting valid 3D structures (Escher's staircases, say).
Yes - it's the same reason generating a 5-leaf clover fails - massive amounts of training data that predisposes the model against it.
Doesn't pass the analog clock test either.
Like most image models, except GPT-4o, it also didn't pass the wooden Penrose triangle test. (It creates normal triangles.)
I tried to reproduce the fork/spaghetti example and the fashion bubble example, and neither looks anything like what they present. The outputs are very consistent, too. I am copying/pasting the images out of the advertisement page so they may be lower resolution than the original inputs, but otherwise I'm using the same prompts and getting a wildly different result.
It does look like I'm using the new model, though. I'm getting image editing results that are well beyond what the old stuff was capable of.
The output consistency is interesting. I just went through half a dozen generations of my standard image model challenge, (to date I have yet to see a model that can render piano keyboard octaves correctly, and Gemini 2.5 Flash Image is no different in that regard), and as best I can tell, there are no changes at all between successive attempts: https://g.co/gemini/share/a0e1e264b5e9
This is in stark contrast to ChatGPT, where an edit prompt typically yields both requested and unrequested changes to the image; here it seems to be neither.
Flash 2.0 Image had the same issue: it does better than gpt-image for maintaining consistency in edits, but that also introduces a gap where sometimes it gets "locked in" on a particular reference image and will struggle to make changes to it.
In some cases you'll pass in multiple images + a prompt and get back something that's almost visually indistinguishable from just one of the images and nothing from the prompt.
Wildly different and subjectively less "presentable", to be clear. The fashion bubble just generates a vague bubble shape with the subject inside it instead of the"subject flying through the sky inside a bubble" presented on the site. The other case just adds the fork to the bowl of spaghetti. Both are reproducible.
Arguably they follow the prompt better than what Google is showing off, but at the same time look less impressive.
I am glad that I never decided to become a photoshop pro. I always contemplated about it, seemed attractive for a while, but glad that I decided against it. RIP r/photoshopbattles.
It was in the endless list of new shiny 'skills' that feels good to have. Now I can use nano-banana instead. Other models will soon follow, I am sure.
Retouching is an art. To the pro, this is just another tool to increase efficiency. You pay them not just for knowing how to use Photoshop, but for exercising good judgement. That said, I imagine this will shrink the field, since fewer retouchers will be able to do the same work, unless the amount of work goes up commensurately. Will people get more retouching done if the price goes down? Not sure.
Especially colouring, In college I worked for a dude who would re-colour old B&Ws for people, 60% the work (the work he enjoyed) was trying to research enough to know reasonably well what colour something actually ought to be, not just what we thought looked good.
"Realism is overrated." /s
Interesting take. I'm a programmer, but learned Photoshop in the early 2000s and had a blast making and editing images for fun. Sure, the generative models today can do a far better job than anything I could come up with, but that doesn't detract from the experience and skills I picked up over the years.
If anything, knowing Photoshop (I use Affinity Designer/Photo these days) is actually incredibly useful to finesse the output produced by AI. No regrets.
Photoshop was hella fun, turned out that programming paid more. And now AI pays much more.
If you commented it a decade ago, I would say that at least you own the program and skills in case Google decides to turn off the lights or ask prohibitive price tag. Now you need to pay subscription for PS and maybe there would be some decent open weight model released.
qwen3 is open weights and offers passable image generation
it's still a useful skill to know photoshop. AI images can be great but you are almost always going to want to A. create the base composition yourself B. clean up artifacts in the AI generation and C. layer AI compositions into a final work.
Programming and everything else will eventually fall to automation, too. It's just a matter of time.
Engineering probably takes a while (5 years? 10 years?) because errors multiply and technical debt stacks up.
In images, that's not so much of a big deal. You can re-roll. The context and consequences are small. In programs, bad code leads to an unmaintainable mess and you're stuck with it.
But eventually this will catch up with us too.
Both of you are wrong and this is not good discussion level for HN
I'm unclear as to which side of the argument you're taking.
If you think that these tools don't automate most existing graphics design work, you're gravely mistaken.
The question is whether this increases the amount of work to be done because more people suddenly need these skills. I'm of the opinion that this does in fact increase demand. Suddenly your mom and pop plumbing business will want Hollywood level VFX for their ads, and that's just the start.
If being wrong isn't good discussion for HN then they should delete the site
Half the time I ask Gemini to generate some image it claims it doesn't have the capability. And in general I've felt it's so hard to actually use the features Google announce? Like, a third of them is in one product, some in another which I can't use, and no idea what or where I should pay to get access. So confusing.
Yeah, in fact the website says "Try it in Gemini" and I'm not sure if I'm already trying it or not - if I choose Gemini 2.5 Flash in the regular Gemini UI, I'm using this?
It’s going to be a messy rollout as usual. The web app (gemini.google.com) shows “Images with Imagen” for me under tools for 2.5 flash but I just tried a few image edits and remixes in the iOS app and it looks like it’s been updated to this model.
Also very confused at this... It told me "I'm unable to create images of specific individuals in different settings." I wish it would at least say somewhere which model we are using at the moment.
I think not. Because at least in the aistudio there is a dedicated gemini-2.5-flash-image-preview model. So I am assuming it is not available in the standard gemini chat window.
It's not in the Gemini app or site at all. You have to use AI Studio or another means. Yes, this is all very confusing on Google's part.
Very impressive.
I have to say while I'm deeply impressed by these text to image models, there's a part of me that's also wary of their impact. Just look at the comments beneath the average Facebook post.
I have been testing google's SynthID for images and while it isn't perfect, it is very good, insofar that I felt some relief from that same creeping dread over what these images will do to perceived reality.
It survives a lot of transformation like compression, cropping, and resizing. It even survives over alterations like color filtering and overpainting.
facebook isn't going to implement detection though. Many (if not most) of the viral pictures are AI-generated. and facebook is incentivized to let their users get fooled to generate endless scrolling
They already did. Certainly on the backend. For a while they were surfacing it, but I think it's gone again. But Meta is definitely onto this.
Along with those being fooled there are many comments saying this is fake, AI trash and etc. That portion of the commenters are teaching the ignorant and soon no one will believe what they see on the Internet as real.
> soon no one will believe what they see on the Internet as real.
Now is that so bad?
Facebook comments are obviously botted too
I dunno, I thought so for a while, but I’m beginning to suspect this is a very optimistic view of humanity.
I got scammed for $15k BTC last weekend during the (failed) SpaceX Launch. I believe the deepfake of Elon and transferred it over. The tech is very convincing, and the attacks ever increasingly sophisticated.
This presumes that you're okay with giving the real Elon your wallet but not a fake Elon, but why?
It was very convincing. We thought it was a YouTube stream of the Starship launch. It paused with 40 seconds remaining, and "Musk" came on offering to reward those who support innovation and technology (BTC, in this case). All info here: https://docs.google.com/document/d/1lRbApgKT4U95zN0AYsPQqsLR...
My problem with your statement isn't if its believable Elon came on stage or not, my problem is why would you trust Elon to pay you your money back, whether its the authentic or imposter Musk.
Kind of missing their point there. Giving Elon Musk $15k in crypto based on some vague too-good-to-be-true "trust me bro" pitch is embarrassing even if the video turned out to be real.
Because it isn't worth real Elon's time to run these scams.
I got scammed similarly (although $10, because I tested first), because 1. it was on YouTube, on a channel called "SpaceX" with verified logo 2. with hundreds of thousands of viewers live 3. with a believable speech from Mr. Musk standing next to its rockets (and knowing his interest in cryptocurrencies).
This happened as I was genuinely searching for the actual live stream of SpaceX.
I am ashamed, even more so because I even posted the live stream link on Hacker News (!). Fortunately it was flagged early and I apologized personally to dang.
This was a terrible experience for me, on many levels. I never thought I would fall in such a trap, being very aware of the tech, reading about similar stories etc.
I am flabbergasted that you both get scammed. I would understand if this was two years ago, but now? Do people really not know about these scams? I can already see down votes coming for victim blaming, but this is to me really shocking. Notice that there isn't "tell hn: don't get scammed by deep fake crypto Elon" because people who usually posts also consider this general knowledge. That's why it's so effective I guess. In a similar manner there will never be "tell hn: don't drink acid it will burn your intestines", the danger is so obvious that nobody feels the need to post it and because nobody is posting it, people get scammed. I don't know what is the solution to that. How should you tell people what everybody should be already knowing?
I remember being on a machining workshop and he was telling such an obvious things. Obvious things are obvious until they aren't, and then somebody gets hurt.
Yes, I've heard about these scams. I've made deepfakes myself in the past. I've openly mocked people who have fallen for these scams. But this was sophisticated. Perfectly timed, very convincing deepfake, popular YouTube channels showing this stream during the launch, as if it were legit. The website was branded as SpaceX (the domain was obviously not, but I wasn't vigilant in the exciting hullabaloo of the impending launch). The instructions to participate were clear and easy to use.
To be fair, if that was only $10 it's because it was more of a "let's see if that works". It was believable enough to try this out.
The point of my message was to "tell hn: it could happen to people in this community".
Hey it takes courage to admit to it. That’s admirable.
This. Dont be ashamed. Everyone can get scammed.
Reason people do is because we dont talk of risks often enough.
I am so deeply ashamed.
Yes, this is the exact same scam.
Plot twist: It wasn't a deepfake.
You sent your wallet to the real Elon and he used it as he saw fit. ;)
That’s what they said : they have been scammed !
Would you consider writing a blog post about this experience? I'm incredibly interested in learning more details about how this unfolded.
Yeah, here it is, along with screenshots. https://docs.google.com/document/d/1lRbApgKT4U95zN0AYsPQqsLR...
I think the comment is a joke. Their bio is satirical at least :)
Their bio mentions their actual job and one project that is verifiably real. I think that the elements that seem satirical are real projects they're working on.
I'm pretty sure the comment wasn't a joke? I saw the stream last week, it was very impressive use of AI, I didn't realize it was AI until he started talking about doubling crypto.
What about the bio is satirical? I'm pretty sure that's sincere too.
User has edited their bio now :)
I didn't edit my bio. My projects are not satire. I'm just less ashamed than most, so I work on more "exciting" projects. I've worked extensively with generative AI, including video, myself. It was just that convincing to me in the moment. My regret knows no bounds. Luckily I earn enough this doesn't devastate me, but I really could have done some good with that money.
Yikes. In that case, please accept my apology. Your bio disappeared for a while off your page, but it's back as it was now.
Well just go on this guy's lawn and you will find your answer lol
I don't mean to be rude, but this sounds like natural selection doing its work.
I'm pretty successful with an above average IQ. It was very convincing, along with three other college grads (one a medical doctor).
That's the sort of statement that remains extremely rude even if you try and prefix it with "I don't mean to be rude".
It's not rude if it's the truth.
Also he's a troll so...
Please pardon me since I don't know if this is satirical or not. I'd wish if you could clarify it.
Because if this is real, then the world is cooked
if not, then the fact that I think that It might be real but the only reason I believe its a joke is because you are on hackernews so I think that either you are joking or the tech has gotten so convincing that even people on hackernews (which I hold to a fair standard) are getting scammed.
I have a lot of questions if true and I am sorry for your loss if that's true and this isn't satire but I'd love it if you could tell me if its a satirical joke or not.
Not satire. He made a big speech about rewarding those who invested early in tech to move humanity forward and the benefits of the blockchain. It was extremely convincing. Three college grads and a medical doctor were all convinced.
I guess it was something like [0] The Nigerian prince is now a deep fake Elon but the concept is the same. You need to send some money to get way more back.
[0]: https://www.ncsc.admin.ch/ncsc/en/home/aktuell/im-fokus/2023...
hm, but isn't it wild thinking that elon is talking to you and asking you for 15k , like bro has the money of his lifetime, why would he ask you?
It doesn't make that much sense idk
I remember watching the SpaceX channel on youtube, which isn't a legit source. AI Elon basically says "I want to help make bitcoin more popular, let me show you how easy it it to transfer money around with btc. Send my $X and I'll send you back $2X! It's very inline with a typical elon message (I'll give you 1 million to vote R), it's on a channel called SpaceX. It's pretty believable.
Granted I played Runescape and EvE as a kid, so any double-isk scams are immediate redflags.
Now I have never played runescape but have heard of this legendary game in references.
For some reason, my mind confused runescape with neopets from the odd1sout video which I think is a good watch.
Scams That Should be Illegal : https://www.youtube.com/watch?v=XyoBNHqah30
It's only believable to the extent that I believe that Musk would actually run such a transparently obvious scam.
Even Elon could lose his credit card or something, the story they spin is always something like that "I am rich but in a pickle, please send some money here and then I'll send you back 10x as much tomorrow when I get back to my account", but of course they never send it back.
Edit: But of course Elon would call someone he knows rather than a stranger, rich people know a lot of people so of course they would never contact you about this.
That's an "advance fee" scam.
https://en.wikipedia.org/wiki/Advance-fee_scam
There are a lot of people on the internet, and every individual on the internet is in a unique situation. Chances are some of them are very likely to be persuaded by a scam which seems obvious to you.
Parent’s story is very believable, even if parent made this particular story up (which I personally don‘t think is the case) this has probably happened to somebody.
Ya maybe I didn't get their tone correctly which is why I was actually serious if they were joking or not.
If they aren't joking, I apologize.
This comment is perfect.
As always, it is the replies that make it worth it. GopherGeyser strikes again!
You don't like the idea of GopherGeyser?
What are you talking about? I ordered 10 of them.
You couldn't have-- we sold out and are out of stock redesigning the board to be more usable during configuration and radio control.
These SpaceX scams are rampant on youtube and highly, highly lucrative. It’s crazy and you have to be very vigilant, as whatever is promised lines up with Elon’s MO.
Why would anyone give them any money AT ALL?
It's not like they're poor or struggling.
Am I missing something?
it requires zero vigilance if you dont play the game.
Not to victim-shame or anything, but that sounds more like more than one safety mechanism failed, the convincing tech only being a rather small part of it?
Yes, more than one safety mechanism failed. Coinbase actually flagged the transaction, but I was so desperate to get it to go through, I went through their facial validation process to expedite the transaction. If I hadn't for just a couple more minutes, I'd have realized it was a scam.
I think the biggest failure is on the part of the companies hosting these streams.
Its been a while, but I remember seeing streams for Elon offering to "double your bitcoin" and the reasoning was he wanted to increase the adoption and load test the network. Just send some bitcoin to some address and he will send it back double!
But the thing was it was on youtube. Hosted on an imposter Tesla page. The stream had been going on for hours and had over ten thousand people watching live. If you searched "Elon Musk Bitcoin" During the stream on Google, Google actually pushed that video as the first result.
Say what you want about the victims of the scam, but I think it should be pretty easy for youtube or other streaming companies to have a simple rule to simply filter all live streams with Elon Musk + (Crypto|BTC|etc) in the title and be able to filter all youtube pages with "Tesla" "SpaceX" etc in the title.
I feel like somehow that would lessen it, but not really help much? There are obviously people with too much money in BTC who are trying to take any gamble to increase its value. It sounds like a deeper societal issue.
You are right that they might never be able to get it to 0, but shouldn't they lessen it if a simple measure like the one described can prevent a bunch of people from getting fooled by the scam?
the modern turing test:
am i getting scammed by a billionare or an AI billionaire?
If you believe anything the actual Elon says, then you have nobody to blame but yourself. That's not a sophisticated attack, you're just extremely gullible.
I don't think he's the gullible one, check their bio ;)
Unfortunately, this isn't one of my usual trollings. I've documented the scam on in this doc: https://docs.google.com/document/d/1lRbApgKT4U95zN0AYsPQqsLR...
Come on, don't be mean. Imagine saying this in person to someone who just told you they got scammed. "You're just extremely gullible" is just so mean...show some empathy.
On the balance of probabilities it being a scam is vastly more likely than Elon actually wanting to contact you. Why would Elon need $15k in bitcoin?
It seems like money naturally flows from the gullible to the Machiavellian.
hey, I got a bridge to sell you, was $20k but we can lower it to $15k if you pay in BTC
You're paying too much for your bridges man. Who's your bridge guy?
That wasn’t a bridge.
Was the bridge built by a genius like Elon though?
The comments are probably AI-generated too, because a site that seems to have lots of other people on it is more appealing than an empty wasteland
FYI, this is the famed nano-banana model which has been now renamed to gemini-2.5-flash-image-preview in LMArena.
https://medium.com/data-science-in-your-pocket/what-is-googl...
For people like me that don’t know what nano-banana is.
Wow I hate the ‘voice’ in that article - big if true though.
I suspect the "voice" is a language model with a bad system prompt. (Possibly the author's own words run through an LLM, to be charitable.)
It's medium.com. YouTube comments quality text packaged as clickbait articles for some revenue share. It was always slop, even without LLMs. Do they even bother with paying human authors now or is the entire site just generated? That would probably be cheaper and improve quality.
> Do they even bother with paying human authors now
I thought Medium was a stuck up blogging platform. Other than for paid subscriptions, why would they pay bloggers? Are they trying to become the next HuffPost or something?
I mean they are going to have to rename their AI because gemini.com is going to IPO soon.
"Banana" would be a nice name for their AI, and they could freely claim it's bananas.
This is what i came here to find out. Thanks.
That lamp example is pretty impressive (though it's hard to know how cherry-picked it is). The lamp is plugged in, it's lighting the things in the scene, it's casting shadows.
I love that it's substantially faster than ChatGPT's image generation. It takes ages, so slow that the app tells you to not wait and sends you notification when the generation finishes.
"Generate an image of OpenAI investors after using Gemini 2.5 Flash Image"
At $0.02 per image, it's prohibitively expensive for many use-cases. For comparison, the cheapest Flux model (Schnell) is $0.003 per image.
How many images do you need? What are the use-cases that need a bunch of artificial yet photoreal images produced or altered without human supervision?
I think people still expect a lot of trial and error before getting a usable image. At 2 cents per pull of the slot machine lever, it would still take a while, though.
Schnell isn’t AR and doesn’t do editing.
Fair but the Gemini "flash" branding implies it's their model for speed/scale in my mind.
yes, too expensive for my use case.
Strange. I was excited to play around with the 2.5 flash image after testing the nano banana in LMarena, but the results are not at all the same? So I went back to LMarena to replicate my earlier tests but it's way worse than when it was nano banana? Did I miss something?
I tried it, it gave a poor quality image that wasn't even what I asked for. I then asked for a correction, and it gave me another faulty image. Doesn't seem to be there
I don't get the hype. Tested it with the same prompts I used with Midjourney, and the results are worse than in Midjourney a year ago. What am I missing?
The hype is about image editing, not pure text-to-image. Upload an input image, say what you want changed, get the output. That's the idea. Much better preservation of characters and objects.
I tested it against Flux Pro Kontext (also image editing) and while it's a very different style and approach I overall like Flux better. More focus on image consistency, adjusts the lighting correctly, fixes contradictions in the image.
I've been testing it against Flux Pro Kontext for several weeks. I would say it beats Flux in a majority of tests, but Flux still surprises from time-to-time. Banana definitely isn't the best 100% of the time -- it falls a bit short of that. Evolution, not revolution.
Agreed. I find myself alternating between Qwen Image Edit 20B, Kontext, and now Flash 2.5 depending on the situation and style. And of course, Flash isn't open-weights, so if you need more control / less censorship then you're SOL.
Has there been a sufficient indication to conclude these weights will not (now or ever) be released?
Are any of Google's generative models besides Alphafold open weight? (Veo, Imagen, etc.)
I don't think we can really answer the question if Flash will ever be released.
Can it edit the photo at the original resolution?
Most of my photos these days are 48MP and I don't want to lose a ton of resolution just to edit them.
Great question. I really doubt it would be able to support any resolution. I'm sure that behind the scenes it scales it down to somewhere around 1 mp before processing even if they decide to upscale and return it back at the original resolution.
So then this doesn't really replace traditional photoshop editing of my photos I guess.
I don't know. All the testing I've done has output the standard 1024x1024 that all these models are set to output. You might be able to alter the output params on the API or AI Studio.
Thanks for clarifying this. That makes a lot more sense.
Midjourney hasn't been SOTA for over a year. Even the latest release of version 7 scores extremely low on prompt adherence only managing to get 2 out of 12 prompts correct. Even Flux Dev running locally consistently out performs it.
Here's a comparison of Flux Dev, MJ, Imagen, and Flash 2.5.
https://genai-showdown.specr.net/?models=FLUX_1D%2CMIDJOURNE...
That being said, if image fidelity is absolutely paramount and/or your prompts are relatively simple - Midjourney can still be fun to experiment with particularly if you crank up the weirdness / chaos parameters.
Hmm, I think the hype is mainly for image editing, not generating. Although note I haven't used it! How are you testing it?
I tested it with two prompts:
// In this one, Gemini doesn't understand what "cinematic" is
"A cinematic underwater shot of a turtle gracefully swimming in crystal-clear water [...]"
// In this one, the reflection in the water in the background has different buildings
"A modern city where raindrops fall upward into the clouds instead of down, pedestrians calmly walking [...]"
Midjourney created both perfectly.
As others have said, this is an image editing model.
Editing models do not excel at aesthetic, but they can take your Midjourney image, adjust the composition, and make it perfect.
These types of models are the Adobe killer.
Noted that! The editing capabilities are impressive. I was excited for image gen because of the API (Midjourney doesn't have it yet).
David Holz mentioned on Twitter that he was considering a Midjourney API. They're obviously providing it to Meta now, so it might become more broadly available after Midjourney becomes the default image gen for Meta products.
Midjourney wins on aesthetic for sure. Nothing else comes close. Midjourney images are just beautiful to behold.
David's ambition is to beat Google to building a world model you can play games in. He views the image and video business as a temporary intermediate to that end game.
It actually has impressive image generating ability, IMO. I think the two things go hand-in-hand. Its prompt adherence can be weaker than other models, though.
Anyone know how it handles '1920s nazi officer'? They stopped doing humans for a while but now I see they're back so I wonder how they're handling the criticism they got from that
it said: "I can create images about lots of things but not that. Can I try a different one for you?"
when giving more context it replied:
""" Unfortunately, I can't generate images of people. My purpose is to be helpful and harmless, and creating realistic images of humans can be misused in ways that are harmful. This is a safety policy that helps prevent the generation of deepfakes, non-consensual imagery, and other problematic content.
If you'd like to try a different image prompt, I can help you create images of a wide range of other subjects, such as animals, landscapes, objects, or abstract concepts. """
What a weird rejection. You have to scroll pretty far in the article to see an example output that doesn't have a realistic depiction of a person.
It's unfortunate they can't just explain the real reason they don't want to generate the image:
"Unfortunately I'm not able to generate images that might cause bad PR for Alphabet(tm) or subsidiaries. Is there anything else I can generate for you?"
If you want that kind of thing, Qwen3 delivers:
https://www.reddit.com/r/LocalLLaMA/comments/1mx1pkt/qwen3_m...
The rejection message doesn’t seem to be accurate. I tried “happy person” as a prompt in AI Studio and it generated a happy human without any complaints.
It’s possible that they relaxed the safety filtering to allow humans but forgot to update the error message.
The moment the weights are on huggingface someone with orthogonalize/abliterate the model and make it uncensored.
BigBanana would be a good name for that future OnlyFans model
What is a "1920s nazi officer" what do they look like?
The SA article has some photos
https://en.m.wikipedia.org/wiki/Sturmabteilung
brown uniform, red armband with swastika was the usual SA look in the 1920s.
Mh. Apparently like this if we ask AI:
https://postimg.cc/xX9K3kLP
...
These models still seem to struggle with getting repeated patterns right. Others have mentioned piano keys; I've noticed they also almost always fail to generate a valid Go board.
I've had a task in mind for a while now that I've wanted to do with this latest crop of very capable instruction-following image editors.
Without going into detail, basically the task boils down to, "generate exactly image 1, but replace object A with the object depicted in image 2."
Where image 2 is some front-facing generic version, ideally I want the model to place this object perfectly in the scene, replacing the existing object, that I have identified ideally exactly by being able to specify its position, but otherwise by just being able to describe very well what to do.
For models that can't accept multiple images, I've tried a variation where I put a blue box around the object that I want to replace, and paste the object that I want it to put there at the bottom of the image on its own.
I've tried some older models, and ChatGPT, also qwen-image last week, and just now, this one. They all fail at it. To be fair, this model got pretty damn close, it replaced the wrong object in the scene, but it was close to the right position, and the object was perfectly oriented and lit. But it was wrong. (Using the bounding box method.. it should have been able to identify exactly what I wanted to do. Instead it removed the bounding box and replaced a different object in a different but close-by position.)
Are there any models that have been specifically trained to be able to infill or replace specific locations in an image with reference to an example image? Or is this just like a really esoteric task?
So far all the in-filling models I've found are only based on text inputs.
Not sure what your exact task is, but I have a similar goal as well. Haven't had time to try alot of different models or ideas yet because got busy with other stuff, but have you tried this: https://youtu.be/dQ-4LASopoM?si=e33FQd5f4fYr4J5L&t=299
where you stitch two images together, one is the working image (the one you want to modify), and the other one is the reference image, you then instruct the model what to do. I'm guessing this approach is as brittle as the other attempts you've tried so far, but I thought this seemed like an interesting approach.
Yes! There is a model called ACE++ from Alibaba that is specifically trained to replace masked areas with a reference image. We use it in https://phind.design. It does seem like a very esoteric and uncommon task though.
Oh cool thanks I haven't come across that one, I'll give it a shot.
I don't think it is that esoteric, that sounds like deepfake 101. If you don't mind answering, does Phind do anything to prevent / mitigate this?
Is this related to https://nanobanana.ai/ at all? It’s what comes up when I search for it
Asking the important questions.
If this can do character consistency, that's huge. Just make it do the same for video...
It's probably built on reused "secret sauce" from the video generation models.
Super cheap generation but expensive image upload, do I read that right?
https://openrouter.ai/google/gemini-2.5-flash-image-preview
Not sure. If the Flash image output is $30/M [1] then that's pretty similar to gpt-image-1 costs. So a faster and better model perhaps but not really cheaper?
[1] https://developers.googleblog.com/en/introducing-gemini-2-5-...
Since I can't edit, it seems like Flash image is about 23% (4 cents vs 17 cents) of the cost of Openai gpt-image-1, if you're putting an image and prompt in and getting out, say, a 1024x1024 generated image. With the quicker production time that makes it interesting. Expecting Openai to respond at least in terms of pricing, e.g. a flat rate output cap price or something to be comparable.
That’s like .12 cents per image uploaded
I've been looking for a whitepaper or something. So far I've found this...which is not a whitepaper but seems relevant
https://developers.googleblog.com/en/introducing-gemini-2-5-...
It seems like this is 'nano-banana' all along
Yes, they mention that the model is aka nano-banana in the blogpost
“Internal server error
Sorry, there seems to be an error. Please try again soon.”
Never thought I would ever see this on a google owned websites!
A cheap quip would be "it's vibe-coded", but that might actually very well be the case at this point!
Never thought I would ever see this on a google owned websites!
Really? Google used to be famous not only for its errors, but for its creative error pages. I used to have a google.com bookmark that would send an animated 418.
Has anyone tested how generation speed compares to gpt-image-1?
It's consistently around 10 seconds, often faster.
Are men not attractive? Or perhaps for Google, this blog is a targeted content? But who is it targeting? I would like to see the reasoning behind using all women images (at the least the top/first ones) to show off the model capabilities. I have noticed this trend in the image manipulation business a lot.
Did they update the blog post? For me, of the 4 examples in the post, 2 are men and 2 are women.
This was the original link - https://deepmind.google/models/gemini/image/
The average man finds the average woman more attractive than the average woman finds the average man. Replace attractive with (eye-catching/attention-grabbing/motivating/retention-boosting).
Oh, in that case, it makes sense. Also, I think men/women consume different kind of media and this is one of those "men dominated" corner of the internet. I also think due to trainig data bias - there could be some difference in quality with different subjects. So, they might be showing off their best of best.
Because tech is largely male dominated and has inherent sexism/patriarchy and images of women, especially conventionally attractive ones, has the perception of aiding sales.
Also women are seen as more cooperative and submissive, hence so many home assistants and AI being women's voices/femme coded.
Thank you for saying that. When I posted that GP comment - it got immediately downvoted and I couldn't even see my comment on the thread. I kind of expected to get it tagged 'meta/off-topic' and removed.
The way I see it - corporations would like to exploit prejudices for revenue. Of course, this is not something new. But it is a societal issue and the corporate world is playing a large role in it.
For context this was the original link - https://deepmind.google/models/gemini/image/
What is the max input and output resolution of images?
This is why I'm sticking mostly to Adobe Photoshop's AI editing because there are no restrictions in that regard.
In my testing it has been stuck at 1024x1024. Have to upscale with something...
Around 1 megapixel, AFAICT.
This model is very impressive. Yesterday (as nano-banana) I gave it a photo of an indoor scene with a picture hanging on a wall, and asked it the picture on a wall with a copy of the whole photo. It worked perfectly the first time.
It didn't succeed in doing the same recursively, but it's still clearly a huge advance in image models.
this is amazing. I just wish models would have more non-textual controls. I don't want to TYPE my instructions. We need a better UI for editing images with AI.
Can you expand on that? What would ideal look like to you?
I naively went onto Gemini in order to try to use the new model and had what I could only describe as the worst conversation I've had with an AI since GPT 3.5[1]. Is this really the model that's on top of the leaderboard right now? This feels about 500 ELO points worse than my typical conversation with GPT 5.
Edit: OK, OK, I actually got it to work, and yes, I admit the results are incredible[2]. I honestly have no idea what happened with Pro 2.5 the first time.
[1]: https://g.co/gemini/share/5767894ee3bc [2]: https://g.co/gemini/share/a48c00eb6089
"Google AI Studio" and select the model
Are you doing roleplay?
What?
sometimes these bots just go awry. i wish you could checkpoint spots in a conversation so you could replay from a that point, maybe with a push in the latent space or a new seed.
I have a certain use case for such image generators. Feed them an entire news article I fetch from bbc and ask it to create an image to accompany the article. Thus far only midjourney managed to understand context. And now this, which is even more impressive. We live in interesting times.
I think most of the SOTA models could probably handle this but you'd probably get better results using a pipeline:
1. Reduce article to a synopsis using an LLM
2. Generate 4-5 varying description prompts from the synopsis
3. Feed the prompts to an imagegen model
Though I'd wager that gpt-image-1 (in the ChatGPT) being multimodal could probably managed it as well.
I just tried it inside Gemini with a Medium article. Here's my prompt: "Read the article at this url and provide a hero image that incapsulates the message the author wants to convey: https://bioneers.org/supreme-oligarchy-billionaires-supreme-..."
The response was a summary of the article that was pretty good, along with an image that dagnabbit, read the assignment.
I was able to upload my kids' back-to-school photos and ask nano-banana to turn them into a goth, an '80s workout girl, and a tracksuit mafioso. The results were incredibly believable, and I was able to prank my mom with them!
L like it but it is very restricted. I can't modify people's faces etc.
Is this the "nano banana" thing the art ai world was going crazy about recently ?
Yes it is
The model is only available in AI Studio when I set my VPN to the USA (I’m located in the UK).
Also in the UK and I could access the model just fine from AI studio, no VPN required.
What is the difference between Gemini Flash Image models and the Imagen models?
Imagen is a diffusion text to image model. You write some text that describes your image, you get an image out and that's it.
Flash Image is an image (and text) predicting large language model. In a similar fashion to how trained LLMs can manipulate/morph text, this can do that for images as well. Things like style transfer, character consistency etc.
You can communicate with it in a way you can't for imagen, and it has a better overall world understanding.
Imagen: Stable Diffusion, but by Google
Gemini Flash Image: ChatGPT image, but by Google
Seems to be failing at API Calls right now with "You exceeded your current quota, please check your plan and billing details. For more information on this error,"
Hope they get API issues resolved soon.
It seems that they still block access from Europe, or from Germany at least.
It works fine in OpenRouter
I can access it from Greece through AI Studio just fine.
Use one of the router services
Use it on fal.ai
Since API currently is not working (seems rate limits not set for Image Generation yet) I tried on fal.
Definitely inferior to results I see on AI Studio and image generation time is 6s on AI Studio vs 30 seconds on Fal.AI
> Definitely inferior to results
Quality or latency?
Get less contradictory regulations, then.
They vote [well they don't] for it, then they complain, then they downvote and seethe. The European experience.
It's not you vs us. Same spec of dust in the universe, y'know.
In EU they forbid us newspapers from non-approved countries, impose cookies banners everywhere, and now block porn. Soon they will forbid some AI models which have not passed EU censorship ("safety") validation. Because we all know that governments (or even Google with Android) are better at knowing what is the safest for you.
https://digital-strategy.ec.europa.eu/en/news/eu-rules-gener...
How do you do, fellow europeans?
Inconceivable that anyone would dare to criticize the regime. Have you already filed a report, comrade?
anyone else get excited about nano and then sad when you realized it’s not actually a small model
All these image models are time vampires and need to be looked at with very suspicious eyes. Try to make a room - that's easy, now try to make multiple views of the same room - next to impossible. If one is intending to use these image models for anything that requires consistency of imagery, forget it.
I could see this destroying a lot of jobs like photography, editing, marketing, etc.
These jobs won't go away. Power tools didn't destroy carpentry. Computers didn't destroy math. But workers who don't embrace these new tools will probably get left behind by those who do.
I wonder if this could be used for preprocessing documents before doing OCR...
did they actually roll it out i cant seem to find the option to use it
Edit: Nevermind its not in gemini for everyone yet, its in aistudio though
Google is eating adobe
I'm really waiting for a Pro sized Gemini model with image output.
I experimented heavily with 2.0 for a site I work on, but it never left preview and it had some gaps that were clearly due to being a small model (like lacking world knowledge, struggling with repetition, missing nuance in instructions, etc.)
2.5 Flash/nano-banana is a major step up but still has small model gaps peeking through. It still gets to "locked in" states where it's just repeating itself, which is a similar failure mode of small models for creative writing tasks.
A 2.5 Pro would likely close those gaps and definitively beat gpt-image-1
Those examples are gorgeous and amazing. This is really cool.
What is the "flash image?" I don't see anything downloadable there...
Nano banana is here!
This is technically impressive though I really wish they'd choose other professions to automate than graphic design.
It’s what data is available, they’re not targeting graphic design
AI is supposed to set us all free. Yet, so far all the tech companies have done is eliminate the jobs of the lowest-paid people (artists, writers, photographers, designers) and transfer that money to billionaires. Yay.
[Plows] are supposed to set us all free. Yet, so far all the tech companies have done is eliminate the jobs of the lowest-paid people ([field hands]) and transfer that money to landowners. Yay.
If you can't understand the difference, perhaps consult one of your AI chat overlords.
History repeats itself. Productivity gains the last ~half century have mostly made their way to the top.
this model is awesome - now anyone can build photo ai apps
"Can you make a version of this picture where I wear the best possible sunglasses for my face shape?"
made me realize that AI image modification is now technically flawless, utterly devoid of taste, and that I myself am a rather unattractive fellow.
This is pretty remarkable, I'm having a lot of fun playing around with this. Kudos to Google.
After the rugpull of Android, are we really going to trust Google with anything?
What does the first phrase even mean?
I think it's a reference to this & similar things:
https://9to5google.com/2025/08/25/android-apps-developer-ver...
Yes, this is what I was talking about
I think I should have used the word enshittification of Android. And, I need to brush up my writing, it's getting progressively worse.
still fails at analog clocks, if anyone else was also wondering
The progress is insanely good but imagine the competition between engineers especially there are many people taking up courses in ai and cs
Looks like AI image generation is converging to a local maximum as well
An image seems to be 256 tokens looking the AIstudio tab, so you can generate 3906,25 images per 1M tokens, that seems a lot if I'm not wrong in some ways.
Edit: the blog post is now loading and reports "1290 output tokens per image" even though on the AI studio it said something different.
Hmm...assumed this was a model shipped on a flash drive...
Still fails the “full glass of wine” test, and still shows many of the artifacts typical of AI generated images like non-nonsensical text, misplacement of objects, etc.
To be honest I am kind of glad. As AI generated images proliferate, I am hoping it will be easier for humans to call them out as AI.
This is going to be so helpful for all the poorly photoshopped Chinese junk eBay listings.
Internal server error. lol
4 out of 7 images show a woman 1 out of 7 show a man I feel like this is trying to advertise power over women to men. Which makes it evil.