OpenAI releases image generation in the API
308 comments
·April 24, 2025cuuupid
vasco
Turns out AI alignment just means "align to the customer current subscription plan", and not protecting the world. Classic.
ben_w
"Alignment with who?" has always been a problem. An AI is a proxy for a reward function, a reward function is a proxy for what the coder was trying to express, what the coder was trying to express is a proxy for what the PM put on the ticket, what the PM put on the ticket is a proxy for what the CEO said, what the CEO said is a proxy for shareholder interests, shareholder interests are a proxy for economic growth, economic growth is a proxy for government interests.
("There was an old lady who swallowed a fly, …")
Each of those proxies can have an alignment failure with the adjacent level(s).
And RLHF involves training one AI to learn human preferences, as a proxy for what "good" is, in order to be the reward function that trains the actual LLM (or other model, but I've only heard of RLHF being used to train LLMs)
babyent
Ethics “concerns” from for-profit companies is 100% marketing and 0% real.
Do people actually fall for these lol? Yes they do and it works to raise interest and get additional funding.
bilbo0s
More accurate to call it “alignment for plebes and not for the masters of the plebes”. Which I think we all kind of expect coming from the leaders of our society. That’s the way human societies have always worked.
I’m sure access to military grade tech is only one small slice in the set of advantages the masters get over the mastered in any human society.
wahnfrieden
That’s ahistorical see Dawn of Humanity for rebuttal to naturalness of imposed hierarchy
7bit
"Protecting the world" would require a common agreement on morals and ethics. OpenAI shitting it's pants when asking how to translate "fuck", which OpenAI refused for a very long time, is not a good start.
Morals and ethics are different and I would not want the US to be "protecting the world" with their ridiculous ethics and morals.
sebzim4500
I mean, obviously? AI alignment has always meant alignment with the creator of the model.
Trying to align OpenAI etc. with the rest of humanity is a completely different problem.
consumer451
I've always thought that if a corporate lab achieves AGI and it starts spitting out crazy ideas such as "corporations should be taxed," we won't be hearing about AGI for a while longer due to "alignment issues."
thegreatpeter
Protecting the world?
spiderice
I also wonder what they mean by that. How is the world protected if China has AI that can handle military tasks but the US doesn't?
idiotsecant
Right, proper alignment with quarterly results.
mapt
> I really didn't expect so much paperclip production growth this quarter!
>> How'd you do it?
> I don't know the details. ChatGPT did it for me, this thing's amazing. Our bonuses are gonna be huge this year, I might even be able to afford a lift kit for my truck.
refulgentis
It's "tier 5", I've had an account since the 3.0 days so I can't be positive I'm not grandfathered in, but, my understanding is as long as you have a non-trivial amount of spend for a few months you'll have that access.
(fwiw for anyone curious how to implement it, it's the 'moderation' parameter in the JSON request you'll send, I missed it for a few hours because it wasn't in Dalle-3)
dunkmaster
API shows either auto or low available. Is there another secret value with even lower restrictions?
refulgentis
Not that I know of.
I just took any indication that the parent post meant absolute zero moderation as them being a bit loose with their words and excitable with how they understand things, there were some signs:
1. it's unlikely they completed an API integration quickly enough to have an opinion on military / defense image generation moderation yesterday, so they're almost certainly speaking about ChatGPT. (this is additionally confirmed by image generation requiring tier 5 anyway, which they would have been aware of if they had integrated)
2. The military / defense use cases for image generation are not provided (and the steelman'd version in other comments is nonsensical, i.e. we can quickly validate you can still generate kanban boards or wireframes of ships)
3. The poster passively disclaims being in military / defense themself (grep "in that space")
4. it is hard to envision cases of #2 that do not require universal moderation for OpenAI's sake, i.e. lets say their thought process is along the lines of: defense/military ~= what I think of as CIA ~= black ops ~= image manipulation on social media, thus, the time I said "please edit this photo of the ayatollah to have him eating pig and say I hate allah" means its overmoderated for defense use cases
5. It's unlikely openai wants to be anywhere near PR resulting from #4. Assuming there is a super secret defense tier that allows this, it's at the very least, unlikely that the poster's defense contractor friends were blabbing about about the exclusive completely unmoderated access they had, to the poster, within hours of release. They're pretty serious about that secrecy stuff!
6. It is unlikely the lack of ability to generate images using GPT Image 1 would drive the military to Chinese models (there aren't Chinese LLMs that do this! even if they were, there's plenty of good ol' American diffusion models!)
samtp
What's a good use case for a defense contractor to generate AI images besides to include in presentations?
aigen000
Fabricating evidence of weapons of mass destruction in some developing nation.
I kid, more real world use cases would be for concept images for a new product or marketing campaigns.
toasteros
...you can do that with a pencil, though.
What an impossibly weird thing to "need" an LLM for.
subroutine
Think of all the trivial ways an image generator could be used in business, and there is likely a similar use-case among the DoD and its contractors (e.g. create a cartoon image of a ship for a naval training aid; make a data dashboard wireframe concept for a decision aid).
golergka
Input one image of a known military installation and one civilian building. Prompt to generate a similar _civilian_ building, but resembling that military installation in some way: similar structure, similar colors, similar lighting.
Then include this image in a dataset of another net with marker "civilian". Train that new neural net better so that it does lower false positive rate when asked "is this target military".
aprilthird2021
You'll never get promoted thinking like that! Mark them all "military", munitions sales will soar!
cuuupid
The very simple use case is generating mock targets. In movies they make it seem like they use mannequin style targets or traditional concentric circles but those are infeasible and unrealistic respectively. There's an entire modeling industry here and being able to replace that with infinitely diverse AI-generated targets is valuable!
missedthecue
Generating 30,000 unique images of artillery pieces hiding in underbrush to train autonomous drone cameras.
Barrin92
I don't really understand the logic here. All the actual signal about what artillery in bushes look like is already in the original training data. Synthetic data cannot conjure empirical evidence into existence, it's as likely to produce false images as real ones. Assuming the military has more privileged access to combat footage than a multi-purpose public chatbot I'd expect synthetic data to degrade the accuracy of a drone.
gmerc
Unreal, Houdini and a bunch of assets do this just fine and provide actually usable depth / infrared / weather / fog / TOD / and other relevant data for training - likely cheaper than using their API
See bifrost.ai and their fun videos of training naval drones to avoid whales in an ethical manners
junon
It's probably not that, but who knows.
The real answer is probably way, way more mundane - generating images for marketing, etc.
krzat
Interesting. Let's say we have those and also 30k real unique images, my guess is that real ones would have more useful information in them, but is this measurable? And how much more?
cortesoft
If the model can generate the images, can't it already recognize them?
ZeroTalent
Manufacturing consent
matheusmoreira
Reality is turning into some kind of Hideo Kojima game.
rnd0
Literally how it will be used; you are correct.
potatoman22
Generating or augmenting data to train computer vision algorithms. I think a lot of defense problems have messy or low data
aprilthird2021
Generating pictures of "bad guy looking guys" so your automated bombs shoot more so you sell more bombs
throwaway314155
> 4 different defense contractors in the last day
Now I'm just wondering what the hell defense contractors need image generation for that isn't obviously horrifying...
Aeolun
“Generate me a crowd of civilians with one terrorist in.”
“Please move them to some desert, not the empire state building.”
“The civilians are supposed to have turbans, not ballcaps.”
ziml77
That's very outdated, they're absolutely supposed to be at the Empire State Building with baseball caps now. See: ICE arrests and Trump's comment on needing more El Salvadoran prison space for "the homegrowns"
vFunct
Show me a tunnel underneath a building in the desert filled with small arms weapons with a poster on the wall with a map of the United States and a label written with sharpie saying “Bad guys here”. Also add various Arabic lettering on the weapons.
null
renewiltord
They make presentations. Most of their work is presentations with diagrams. Icons.
qatanah
All I can think of is image generation of potential targets like ships, airplane, airfield and feed them to their satellite or drones for image detection and tweak their weapons for enhance precision.
daemonologist
I think the usual computer vision wisdom is that this (training object detection on generated imagery) doesn't work very well. But maybe the corps have some techniques that aren't in the public literature yet.
morleytj
It's probably horrifying!
sieabahlpark
[dead]
rchaud
In 2024, the Pentagon carved out an exception for themselves on the Huawei equipment ban [0]
I would imagine defense contractors can cut deals for similar preferential treatment with OAI and the like to be exempt from potentially copyright-infringing uses of their API.
[0]https://fortune.com/asia/2024/07/03/pentagon-huawei-ban-nati...
benterix
That tier is also available for text generation, not just images.
null
0rzech
One of the dangers of completely relying on AI is that someone else gets to decide what we can generate with their models.
giancarlostoro
Just ask Microsoft about Tay. On the one hand, I understand why you want some censoring in your model, on the other, I think it also cripples your models in unexpected ways, I wonder if anyone's done such research, compare two models by the same source training data, one with censoring of offensive things, the other without. Which one provides more accurate answers?
johnyzee
I wanted to try this in the image playground, but I was told I have to add a payment method. When adding this, I was told I would also have to pay a minimum of $5. Did this. Then when trying to generate an image, I was told I would have to do "verification" of my organization (?). OK, I chose 'personal'. I was then told I have to complete the verification though some third party partner of OpenAI, which included giving permission to process my biometric information. Yeah, I don't want to try this that bad, but now I already paid you and have to struggle to figure out how to get my money back. Horrible UX.
vizzah
Be aware that OpenAI API credits expire after a year. I've added $5 year ago expecting to use the API, but only consumed $.02 or something. The API started throwing out "Too many requests" HTTP error when I needed it again and ooops!.. there were nothing left. All credit has gone.
Wouldn't have expected that from a honest player.
funwares
Big thanks for the heads up, I had no idea about this.
It looks like I will not be able to get any prepaid money back [0] so I will be careful not to put any further money on it.
I guess I better start using some of the more expensive APIs to make it worth the $20 I prepaid.
[0] https://openai.com/policies/service-credit-terms/
4. "All sales of Services, including sales of prepaid Services, are final. Service Credits are not refundable and expire one year after the date of purchase or issuance if not used, unless otherwise specified at the time of purchase."
rideontime
Chargeback. Yes, this may result in your being banned from purchasing any OpenAI services in the future; I would see this as an added benefit to prevent making the same mistake again.
tezza
For the curious I generated the same prompt for each of the quality types. ‘Auto’, ‘low’, ‘medium’, ‘high’.
Prompt: “a cute dog hugs a cute cat”
https://x.com/terrylurie/status/1915161141489136095
I also then showed a couple of DALL:E 3 images for comparison in a comment
echelon
> a cute dog hugs a cute cat
This prompt is best served by Midjourney, Flux, Stable Diffusion. It'll be far cheaper, and chances are it'll also look a lot better.
The place where gpt-image-1 shines if if you want to do a prompt like:
"a cute dog hugs a cute cat, they're both standing on top of an algebra equation (y=\(2x^{2}-3x-2\)). Use the first reference image I uploaded as a source for the style of the dog. Same breed, same markings. The cat can contrast in fur color. Use the second reference image I uploaded as a guide for the background, but change the lighting to sunset. Also, solve the equation for x."
gpt-image-1 doesn't make the best images, and it isn't cheap, and it isn't fast, but it's incredibly -- almost insanely -- powerful. It feels like ComfyUI got packed up into an LLM and provided as a natural language service.
stavros
I wonder if we can use gpt-image-1 outputs, with some noise, as inputs to diffusion models, so GPT takes care of adherence and the diffusion model improves the quality. Does anyone know whether that's at all possible?
AuryGlenz
Sure. I suppose with API support 3 hours ago someone probably made a Comfy node all of 2 hours ago. From there you can either just do a low denoise or use one of the many IP-Adapter type things out there.
levzzz
yes it's what a lot of people have been doing with newer models which have better prompt adherence, passing them through older models with better aesthetics
MoonGhost
Not bad. Photo forums will be soon full of them. Slightly edited to remove metadata and make them look like human made.
latexr
> the same prompt for each of the quality types. ‘Auto’, ‘low’, ‘medium’, ‘high’.
“Auto” is just whatever the best quality is for a model. So in this case it’s the same as “high”.
whywhywhywhy
Crazy even photos have the OpenAI yellow color grade
mclau157
please use BlueSky
film42
I generated 5 images in the playground. One using a text-only prompt and 4 using images from my phone. I spent $0.85 which isn't bad for a fun round of Studio Ghibli portraits for the family group chat, but too expensive to be used in a customer facing product.
sumedh
> but too expensive to be used in a customer facing product.
Enhance headshots for putting on Linkedin.
salomonk_mur
It doesn't keep facial details in the generation. The generated person resembles you but is definitely not you.
anshumankmr
Yeah its very eerie. Though sometimes its very close, like dangerously I feel, I tried once myself and the background was unrealistic (the prompt was me giving a keynote speech for a vision board ) but I looked like... me.
bamboozled
Can't wait to meet people in person who look nothing like their profile pictures on linkedin :)
martin_a
I already did. Looked in the mirror just an hour ago. Strange guy, very tired, never seen him before.
BOOSTERHIDROGEN
is it good?
stavros
No, it can't do detail well, AFAIK the images are produced at a lower resolution and then upscaled. This might be specific to the ChatGPT version, however, for cost cutting.
alasano
I built a local playground for it if anyone is interested (your openai org needs to be verified btw..)
https://github.com/Alasano/gpt-image-1-playground
Openai's Playground doesn't expose all the API options.
Mine covers all options, has built in mask creation and cost tracking as well.
test1235Mega
I really like that you build it, but I'm getting errors "Your organization must be verified to use the model `gpt-image-1"
Can we talk in discord, please?
alasano
I think I linked to the verification process on OpenAI's website in then documentation.
You need to verify your identity with a driver's license or passport with OpenAI to have access to certain things like chain of thought summaries in the API and image generation with the new model.
Nothing I can do there, you gotta verify unfortunately.
Imnimo
I'm curious what the applications are where people need to generate hundreds or thousands of these images. I like making Ghibli-esque versions of family photos as much as the next person, but I don't need to make them in volume. As far as I can recall, every time I've used image generation, it's been one-off things that I'm happy to do in the ChatGPT UI.
minimaxir
As usual for AI startups nowadays, using this API you can create a downstream wrapper for image generation with bespoke prompts.
A pro/con of the multimodal image generation approach (with an actually good text encoder) is that it rewards intense prompt engineering moreso than others, and if there is a use case that can generate more than $0.17/image in revenue, that's positive marginal profit.
theptip
An obvious one is for video games, interactive fiction, that sort of thing. AI dungeon with visuals could be pretty interesting.
brian-armstrong
It's too expensive for that unless you had a pretty generous subscription fee. I think local models are probably best suited for gaming where a decent GPU is already likely present.
theptip
I think there is a niche for both. Local LLMs are orders of magnitude smaller, so you could imagine cloud bursting for the difficult/important work like generating character portraits.
That said it’ll be 10-20x cheaper in a year at which point I don’t think you care about price for this workflow in 2D games.
austhrow743
I use the api because i don’t use chatgpt enough to justify the cost of their UI offering.
reducemore
I’ve built a daily image-based puzzle that’s fully automated, and have been using flux to generate images. I’ve found sometimes they’re just not good enough, so have been doing some manual curation. But, with this new API, I’ll see if it can run by itself again.
marviel
AI-assisted education is promising.
samtp
I'm still struggling to see how you would need thousands of AI generated images rather than just using existing real images for education.
abossy
The company I work for generates thousands of these each week for children's personalized storybooks to help them learn how to read. The story text is the core part of the application, but the personalized images are what make them engaging.
marviel
- personalization (style, analogy to known concepts)
- specificity (a diagram that perfectly encapsulates the exact set of concepts you're asking about)
Etheryte
That is true in a broader sense, but education and abundant money don't generally go hand in hand.
marviel
don't I know it
whatnow37373
"Having trouble with your algebra? MathWiz is having a 20% discount this month only. Only $24.95 / month. This is an excellent deal. Don't you want to improve? Do you want to let your family down, like they thought you would? Or would like me to create an account for you?"
marviel
"Want to get a job? [COLLEGE] is having a 0% discount -- only $200,000 a year! Don't you want to have a place to live? Go horribly in debt, pick a degree that may not matter, all at an age where your Brain has not yet developed fully!"
etc
whywhywhywhy
> where people need to generate hundreds or thousands of these images
Anyone using image gen for real work not just for fun.
Although you're way better off finding your own workflows with local models at that scale.
chipgap98
Interior design, fashion, and advertising all come to mind
aprilthird2021
Imagine a news feed that never ends full of AI slop to sell ads on
minimaxir
Pricing-wise, this API is going to be hard to justify the value unless you really can get value out of providing references. A generated `medium` 1024x1024 is $0.04/image, which is in the same cost class as Imagen 3 and Flux 1.1 Pro. Testing from their new playground (https://platform.openai.com/playground/images), the medium images are indeed lower quality than either of of two competitor models and still takes 15+ seconds to generate: https://x.com/minimaxir/status/1915114021466017830
Prompting the model is also substantially more different and difficult than traditional models, unsurprisingly given the way the model works. The traditional image tricks don't work out-of-the-box and I'm struggling to get something that works without significant prompt augmentation (which is what I suspect was used for the ChatGPT image generations)
raincole
ChatGPT's prompt adherence is light years ahead of all the others. I won't even call Flux/Midjoueny its competitors. ChatGPT image gen is practically a one-of-its-kind unique product on the market: the only usable AI image editor for people without image editing experience.
I think in terms of image generation, ChatGPT is the biggest leap since Stable Diffusion's release. LoRA/ControlNet/Flux are forgettable in comparison.
thegeomaster
Well, there's also gemini-2.0-flash-exp-image-generation. Also autoregressive/transfusion based.
thefourthchime
Such a good name....
Yiling-J
gemini-2.0-flash-exp-image-generation doesn’t perform as well as GPT-4o's image generation, as mentioned in section 5.1 of this paper: https://arxiv.org/pdf/2504.02782. However based on my test, for certain types of images such as realistic recipe images, the results are quite good. You can see some examples here: https://github.com/Yiling-J/tablepilot/tree/main/examples/10...
raincole
It's quite bad now, but I have no doubt that Google will catch up.
The AI field looks awfully like {OpenAI, Google, The Irrelevent}.
yousif_123123
It's also good but clearly not close still. Maybe Gemini 2.5 or 3 will have better image gen.
swyx
> transfusion based.
what is that?
echelon
I'd go out on a limb and say that even your praise of gpt-image-1 is underselling its true potential. This model is as remarkable as when ChatGPT first entered the market. People are sleeping on its capabilities. It's a replacement for ComfyUI and potentially most of Adobe in time.
Now for the bad part: I don't think Black Forest Labs, StabilityAI, MidJourney, or any of the others can compete with this. They probably don't have the money to train something this large and sophisticated. We might be stuck with OpenAI and Google (soon) for providing advanced multimodal image models.
Maybe we'll get lucky and one of the large Chinese tech companies will drop a model with this power. But I doubt it.
This might be the first OpenAI product with an extreme moat.
raincole
> Now for the bad part: I don't think Black Forest Labs, StabilityAI, MidJourney, or any of the others can compete with this.
Yeah. I'm a tad sad about it. I once thought the SD ecosystem proves open-source won when it comes to image gen (a naive idea, I know). It turns out big corps won hard in this regard.
soared
This is a take so incredulous it doesn’t seem credible.
stavros
I can confirm, ChatGPT's prompt adherence is so incredibly good, it gets even really small details right, to a level that diffusion-based generators couldn't even dream of.
mediaman
It is correct, the shift from diffusion to transformers is a very, very big difference.
abhpro
Also chiming in to say you're wrong, I mean they're correct
tacoooooooo
its 100% the correct take
adamhowell
So, I've long dreamed of building an AI-powered https://iconfinder.com.
I started Accomplice v1 back in 2021 with this goal in mind and raised some VC money but it was too early.
Now, with these latest imagen-3.0-generate-002 (Gemini) and gpt-image-1 (OpenAI) models – especially this API release from OpenAI – I've been able to resurrect Accomplice as a little side project.
Accomplice v2 (https://accomplice.ai) is just getting started back up again – I honestly decided to rebuild it only a couple weeks ago in preparation for today once I saw ChatGPT's new image model – but so far 1,000s of free to download PNGs (and any SVGs that have already been vectorized are free too (costs a credit to vectorize)).
I generate new icons every few minutes from a huge list of "useful icons" I've built. Will be 100% pay-as-you-go. And for a credit, paid users can vectorize any PNGs they like, tweak them using AI, upload their own images to vectorize and download, or create their own icons (with my prompt injections baked in to get you good icon results)
Do multi-modal models make something like this obsolete? I honestly am not sure. In my experience with Accomplice v1, a lot of users didn't know what to do with a blank textarea, so the thinking here is there's value in doing some of the work for them upfront with a large searchable archive. Would love to hear others' thoughts.
But I'm having fun again either way.
stavros
That looks interesting, but I don't know how useful single icons can be. For me, the really useful part would be to get a suite of icons that all have a consistent visual style. Bonus points if I can prompt the model to generate more icons with that same style.
throwup238
Recraft has a style feature where you give some images. I wonder if that would work for icons. You can also try giving an image of a bunch of icons to ChatGPT and have it generate more, then vectorize them.
egypturnash
[flagged]
tough
It seems to me like this is a new hybrid product for -vibe coders- beacuse otherwise the -wrapping- of prompting/improving a prompt with an LLM before hitting the text2image model can certainly be done as you say cheaper if you just run it yourself.
maybe OpenAI thinks model business is over and they need to start sherlocking all the way from the top to final apps (Thus their interest on buying out cursor, finally ending up with windsurf)
Idk this feels like a new offering between a full raw API and a final product where you abstract some of it for a few cents, and they're basically bundling their SOTA llm models with their image models for extra margin
vineyardmike
> It seems to me like this is a new hybrid product for -vibe coders- beacuse otherwise the -wrapping- of prompting/improving a prompt with an LLM before hitting the text2image model can certainly be done as you say cheaper if you just run it yourself.
In case you didn’t know, it’s not just wrapping in an LLM. The image model they’re referencing is a model that’s directly integrated into the LLM for functionality. It’s not possible to extract, because the LLM outputs tokens which are part of the image itself.
That said, they’re definitely trying to focus on building products over raw models now. They want to be a consumer subscription instead of commodity model provider.
tough
Right! I forgot the new model was a multi-modal one generating image outputs from both image and text inputs, i guess this is good and price will come down eventually.
waiting for some FOSS multi-modal model to come out eventually too
great to see openAI expanding into making actual usable products i guess
spilldahill
yeah, the integration is the real shift here. by embedding image generation into the LLM’s token stream, it’s no longer a pipeline of separate systems but a single unified model interface. that unlocks new use cases where you can reason, plan, and render all in one flow. it’s not just about replacing diffusion models, it’s about making generation part of a broader agentic loop. pricing will drop over time, but the shift in how you build with this is the more interesting part.
furyofantares
I find prompting the model substantially easier than traditional models, is it really more difficult or are you just used to traditional models?
I suspect what I'll do with the API is iterate at medium quality and then generate a high quality image when I'm done.
vunderba
> Prompting the model is also substantially more different and difficult than traditional models
Can you elaborate? This was not my experience - retesting the prompts that I used for my GenAI image shootout against gpt-image-1 API proved largely similar.
simonw
It may lose against other models on prompt-to-image, but I'd be very excited to see another model that's as good at this one as image+prompt-to-image. Editing photos with ChatGPT over the past few weeks has been SO much fun.
Here's my dog in a pelican costume: https://bsky.app/profile/simonwillison.net/post/3lneuquczzs2...
steve_adams_86
The dog ChatGPT generated doesn't actually look like your dog. The eyes are so different. Really cute image, though.
thot_experiment
Similarly to how 90% of my LLM needs are met by Mistral 3.1, there's no reason to use 4o for most t2i or i2i, however there's a definite set of tasks that are not possible with diffusion models, or if they are they require a giant ball of node spaghetti in comfyui to achieve. The price is high but the likelyhood of getting the right answer on the first try is absolutely worth the cost imo.
varenc
pretty amazing that in ~two years a 15 second latency AI image generation API that cost 4 cents lags behind competitors.
echelon
This product does not lag behind competitors. Once you take the time to understand how it works, it's clear that this is an order of magnitude more powerful than anything else on the market.
While there's a market need for fast diffusion, that's already been filled and is now a race to the bottom. There's nobody else that can do what OpenAI does with gpt-image-1. This model is a truly programmable graphics workflow engine. And this type of model has so much more value than mere "image generation".
gpt-image-1 replaces ComfyUI, inpainting/outpainting, LoRAs, and in time one could imagine it replaces Adobe Photoshop and nearly all the things people use it for. It's an image manipulation engine, not just a diffusion model. It understands what you want on the first try, and it does a remarkably good job at it.
gpt-image-1 is a graphics design department in a box.
Please don't think of this as a model where you prompt things like "a dog and a cat hugging". This is so much more than that.
badmonster
Usage of gpt-image-1 is priced per token, with separate pricing for text and image tokens:
Text input tokens (prompt text): $5 per 1M tokens Image input tokens (input images): $10 per 1M tokens Image output tokens (generated images): $40 per 1M tokens
In practice, this translates to roughly $0.02, $0.07, and $0.19 per generated image for low, medium, and high-quality square images, respectively.
that's a bit pricy for a startup.
m4thfr34k
Isn't there also a cost per image? The pricing page shows $0.25 for a high quality 1536x1024 image. 25 cents per image is ... steep lol
BoorishBears
Cost per image is based on output tokens (because they're output tokens)
jumploops
This new model is autoregression-based (similar to LLMs, token by token) rather than diffusion based, meaning that it adheres to text prompts with much higher accuracy.
As an example, some users (myself included) of a generative image app were trying to make a picture of person in the pouch of a kangaroo.
No matter what we prompted, we couldn’t get it to work.
GPT-4o did it in one shot!
yousif_123123
It's a mix of both it feels to me as I've been testing it. For example, you can't get it to make a clock showing custom time like 3:30, or someone writing with their left hand.. And it can't do follow many instructions or do them very precisely. But it shows that this kind of architecture will be be capable of that if scaled up most likely.
jumploops
These are great tests, thanks for sharing!
And you seem to be right, though the only reference I can find is in one of the example images of a whiteboard posted on the announcement[0].
It shows: tokens -> [transformer] -> [diffusion] pixels
hjups22 on Reddit[1] describes it as:
> It's a hybrid model. The AR component generates control embeddings that then get decoded by a diffusion model. But the control embeddings are accurate enough to edit and reconstruct the images surprisingly well.
[0]https://openai.com/index/introducing-4o-image-generation/
[1]https://www.reddit.com/r/MachineLearning/comments/1jkt42w/co...
yousif_123123
Yes. Also, when testing low vs high, it seems the difference is mainly in the diffusion part, as the structure of the image and the instruction following ability is usually the same.
Still, very exciting and for the future as well. It's still pretty expensive and slow. But moving in the right direction.
n2d4
Source? It's much more likely that the LLM generates the latent vector which serves as an input to the diffusion model.
jumploops
From the GPT-4o System Card Addendum[0]:
> Unlike DALL·E, which operates as a diffusion model, 4o image generation is an autoregressive model natively embedded within ChatGPT.
[0]https://cdn.openai.com/11998be9-5319-4302-bfbf-1167e093f1fb/...
og_kalu
Open AI said it's auto-regressive, the presentation on the app is autoregressive, it's priced auto-regressively.
Why would that be more likely ? It seems like some implementation of bytedance's VAR.
gervwyk
Great svg generation would be far more userful! For example, being able to edit svg images after generated by Ai would be quick to modify the last mile.. For our new website https://resonancy.io the simple svg workflow images created was still very much created by hand.. and trying various ai tools to make such images yielded shockingly bad off-brand results even when provided multiple examples. By far the best tool for this is still canva for us..
Anyone know of an Ai model for generating svg images? Please share.
jjcm
Recraft also has an svg model: https://replicate.com/recraft-ai/recraft-v3-svg
One note with these is most of the production ones are actually diffusion models that get ran through an image->svg model after. The issue with this is that the layers aren't set up semantically like you'd expect if you were crafting these by hand, or if you were directly generating svgs. The results work, but they aren't perfect.
simonw
I was impressed with recraft.ai for SVGs - https://simonwillison.net/2024/Nov/15/recraft-v3/ - though as far as I can tell they generate raster images and then SVG-ize them before returning the result.
tough
SVGFusion https://arxiv.org/abs/2412.10437 which is a new paper from SVGRender group https://huggingface.co/SVGRender
gervwyk
Amazing thanks for sharing! Will have a read. A commercial model would be something that I will pay for!
tough
I don't know about -commercial- offerings but you can try also something like SVGRender which you should be able to run on your own GPU etc https://ximinng.github.io/PyTorch-SVGRender-project/
first paper linked on prior comment is the latest one from SVGRender group, but not sure if any runnable model weights are out yet for it (SVGFusion)
null
vitorcremonez
Try neoSVG or Recraft, it is awesome!
hombre_fatal
I would have expected an API like:
let imageId = api.generateImage(prompt)
let {url, isFinished} = api.imageInfo(id)
let bytes = api.generateImage(prompt)
With Netflix, it makes sense that you can open a connection to some static content and receive gigabytes over it.
But streaming tokens from a GPU is a much more active process. Especially in this case where you're waiting tens of seconds for an image to generate.
starik36
I can understand that for text answers, but what can you possibly do with streaming tokens for images?
radicality
AFAIK, The newer models for image gen like this OpenAI one, don’t actually use the normal diffusion process (image generates all at once from blurry to finished), but use transformer architecture where the full final image is generated from top to bottom, as a stream of ‘tokens’.
That’s why when you generate an image in chatgpt nowadays, it will start displaying in full resolution from the top pixel row and start loading towards the bottom.
sebastiennight
Hmm seems pricey.
What's the current state of the art for API generation of an image from a reference plus modifier prompt?
Say, in the 1c per HD (1920*1080) image range?
minimaxir
"Image from a reference" is a bit of a rabbit hole. For traditional image generation models, in order for it to learn a reference, you have to fine-tune it (LoRA) and/or use a conditioning model to constrain the output (InstantID/ControlNet)
The interesting part of this GPT-4o API is that it doesn't need to learn them. But given the cost of `high` quality image generation, it's much cheaper to train a LoRA for Flux 1.1 Pro and generate from that.
thot_experiment
Reflux is fantastic for the basic reference image based editing most people are using this for, but 4o is far more powerful than any existing models because of it's large scale and cross-modal understanding, there are things possible with 4o that are just 100% impossible with diffusion models. (full glass of wine, horse riding an astronaut, room without pink elephants, etc)
Tiberium
Imagen supports image references in the API as well, just on Vertex, not on Gemini API yet.
BoorishBears
Imagen references don't feel very useful at all. At most it feels like an afterthought meant to make product photoshoots easier.
When this was up yesterday I complained that the refusal rate was super high especially on government and military shaped tasks, and that this would only push contractors to use CN-developed open source models for work that could then be compromised.
Today I'm discovering there is a tier of API access with virtually no content moderation available to companies working in that space. I have no idea how to go about requesting that tier of access, but have spoken to 4 different defense contractors in the last day who seem to already be using it.