OpenAI releases image generation in the API
160 comments
·April 24, 2025cuuupid
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.
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).
missedthecue
Generating 30,000 unique images of artillery pieces hiding in underbrush to train autonomous drone cameras.
junon
It's probably not that, but who knows.
The real answer is probably way, way more mundane - generating images for marketing, etc.
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!
tzury
AI image generation is a "statistical simulator". And when fed with the right information, it can generates pretty close to reality scenery.
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
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!)
subroutine
Do you work with OpenAI models via FedRAMP GGC High Azure? If so I would love to hear more about your experience.
kryogen1c
I'd be interested to hear if that's even possible.
GCCH is typically 6-12 months behind in feature set.
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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.
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.
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morleytj
It's probably horrifying!
renewiltord
They make presentations. Most of their work is presentations with diagrams. Icons.
sieabahlpark
[dead]
kittikitti
This is on purpose so OpenAI can then litigate against them. This API isn't about a new feature, it's about control. OpenAI is the biggest bully in the space of generative AI and their disinformation and intimidation tactics are working.
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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
MoonGhost
Not bad. Photo forums will be soon full of them. Slightly edited to remove metadata and make them look like human made.
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?
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”.
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.
bamboozled
Can't wait to meet people in person who look nothing like their profile pictures on linkedin :)
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.
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.
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.
marviel
- personalization (style, analogy to known concepts)
- specificity (a diagram that perfectly encapsulates the exact set of concepts you're asking about)
austhrow743
I use the api because i don’t use chatgpt enough to justify the cost of their UI offering.
jevogel
Imagine an AI recipe building app that helps you create a recipe with certain ingredients, then generates an image of what the final product might look like.
what
Why do need to know what it looks like? Or are you publishing the recipe without cooking it?
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.
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.
thegeomaster
Well, there's also gemini-2.0-flash-exp-image-generation. Also autoregressive/transfusion based.
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...
thefourthchime
Such a good name....
yousif_123123
It's also good but clearly not close still. Maybe Gemini 2.5 or 3 will have better image gen.
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.
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.
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.
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.
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. These are truly programmable graphics workflows.
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.
gpt-image-1 is a graphics design department in a box.
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...
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.
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.
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!
jeevships
Genuinely curious, why would someone buy from your gpt image wrapper when they can just create it in gpt themselves?
jonahx
Not being glib, but this is like the famous comment when dropbox was first announced: "you can already build such a system yourself quite trivially by getting an FTP account, mounting it locally with curlftpfs, and then using SVN or CVS on the mounted filesystem". [1]
You might say, "but chatGPT is already as dead simple an interface as you can imagine". And the answer to that is, for specific tasks, no general interface is ever specific enough. So imagine you want to use this to create "headshots" or "linkedin bio photos" from random pictures of yourself. A bespoke interface, with options you haven't even considered already thought through for you, and some quality control/revisions baked into the process, is something someone might pay for.
tarikozket
different personas require different UXs. not everyone is going to understand and enjoy the chat interface; many will require a different UX.
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.
claiir
> GoDaddy is actively experimenting to integrate image generation so customers can easily create logos that are editable [..]
I remember meeting someone on Discord 1-2 years ago (?) working on a GoDaddy effort to have customer-generated icons using bespoke foundation image gen models? Suppose that kind of bespoke model at that scale is ripe for replacement by gpt-image-1, given the instruction-following ability / steerability?
verelo
“ Editing videos: invideo enables millions of users to transform their ideas into videos using AI. With the integration of gpt-image-1, the platform now offers improved text generation, fine-grain editing controls, and advanced style guidance.”
Does this mean this also does video in some manner?
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.