Using the grid trick for animations to generate the individual frames has been around for awhile and not specific to ChatGPT: I'm surprised it took this long for one of the official providers to make it explicit. However, adherence between frames is generally tricky, and even in the examples there is a lot of noise between frames although that could be due to compression.
SVG support is interesting but I suspect shenanigans are afoot since that's not how image generation models work, and it would likely strip any SynthID watermarks. It's possible OpenAI has pipelined a raster-to-vector tool that does the conversion automatically. (I developed a similar pipeline and it works extremely well; I'll open source it at some point)
EDIT: Per documentation, there is an explicit `output_format: "svg"`, and I am indeed correct there is raster-to-vector in play:
> The API creates a reference image and uses it to produce the SVG. The quality setting controls that reference image. Decode data[0].b64_json as base64 and save the resulting UTF-8 XML bytes with a .svg extension.
OpenAI claims 50% faster generation with Images 2.6 but curiously price is the same as Image 2.5.
Feels like ai image generation has plateaud.
Coding related have had massive step-up improvements over time.
The same cannot be said for image generation. If anything, I swear it's gone backwards.
It peaked with very early midjourney (like 2022), maybe follow ups with stable diffusion, and then with some of the nano banana models for actual editing. But overall, very lackluster in comparison to other areas.
I miss the outpainting feature they used to have (3 years ago?) in the dall-e days. It feels like tooling overall for image generation has been standing still or almost regressed the past few years, while the quality has improved
Still looks like an eyesore, I genuinely want to know if the engineers who work on the product don't notice it
The model used by codex-cli is still gpt-image-2. https://github.com/openai/codex/blob/f3074e35c079bd8a5e89b03...
The input and output pricing per token remains the same between 2.5 and 2.6, although using their image pricing calculator shows a quadrupling of token usage at low and medium quality settings for 2.6. For e.g. at 1024x1024:
2.5 low, 196 tokens, $0.006
2.6 low, 823 tokens, $0.025
2.5 med, 439 tokens, $0.013
2.6 med, 1449 tokens, $0.043
Interestingly, higher quality settings show no change in token usage between the models.
Decided to try out one of the new features in GPT Image 2.6: the ability to natively generate animated GIF files.
I didn't have high expectations, and I still think you can probably get better results by doing a First-Last-Frame using something like Minimax H3 but I was still rather surprised that it could do it at all.
Here are some of the results. The last one shows its ability to take an existing image and convert it into an animated GIF. It's a picture of my husky inside a snow globe.
I wish it was properly adjusted to design work. I can get some work done with Gemini over multiple prompts, center this, adjust this, keep stylized properties of this, etc.
https://chatgpt.com/share/6aebc6f8-d660-83e8-9cb3-49bdf8caa7...
I guess I should have been careful about “half”?
These models have a hard time imagining men with naturally blond hair getting grey.
Ask HN: Does anyone know whether a Codex subscription can generate images specifying gpt-image-2.6-sunburst without relying on an api_key?
Based on stolen artwork. F*ck this.
Just wasted 4hrs on the model by trying to do consistent sprite sheet art.
Nothing to see here.
Off-topic, but the looping GIFs of stock prices going up / going down remind me of the currently airing anime https://en.wikipedia.org/wiki/FX_Fighter_Kurumi-chan .
I love images 2, my only issue is the iterative changes. I want to change a tiny thing and it changes too or not exactly what I want, end up being a long conversation to get what I desire. I see this new model promises more control in editing, has anybody tried and experienced a decent improvement?
Did a considerably worse job than Image Gen 2.0 on my standard test prompt.
"A macro close-up photograph of an old watchmaker's hands carefully replacing a tiny gear inside a vintage pocket watch. The watch mechanism is partially submerged in a shallow dish of clear water, causing visible refraction and light caustics across the brass gears. A single drop of water is falling from a pair of steel tweezers, captured mid-splash on the water's surface. Reflect the watchmaker's face, slightly distorted, in the curved glass of the watch face. Sharp focus throughout, natural window lighting from the left, shot on 100mm macro lens."
2.5 is better than 2.6
I've been playing with it for the last hour or so. I immediately updated my platform to use both since 2.5 is my primary model (i run a prompt->design site).
After playing with it for an hour, I'm rolling back 2.6-flare to 2.5-flare. I've found 2.6-flare specifically to either be too simplistic in its approaches, or create outputs that are inherently broken in other cases.
Comparison examples: https://diffui.ai/app/canvas/178db5d5-ff87-4b43-aa98-2897773...
2.6-sunburst seems solid however.
Update: seems to be confirmed on arena.ai - 2.5 scores higher than 2.6 https://arena.ai/leaderboard/image/text-to-image
What's the state of the art for image gen? I'm far removed and pretty happy with the free Gemini tier but its notable to me that I rarely see boasting about being "the best image generator yet" and I wonder if that's because they're all just good enough?
The blog post says
> Images 2.6 is available globally today in ChatGPT and Codex across all subscription tiers on desktop, mobile, and web.
But I just updated my codex-cli to the latest version (still 0.166.0) and it is still unable to generate gifs. Very disappointing
How well does this handle SVG generation? Does it perform better than existing LLMs when asked to create SVGs?
On a phone, if you share a gif, it creates a link to ChatGPT.com with a static image. You can also save the image to photos and share directly from there which feels like an unnecessary step.
It feels like a sleazy pattern and defeats the purpose of why I’d want to generate a gif in the first place, which to make clear is likely going to be to share with friends in a chat. I’m not interested in driving traffic to ChatGPT.com to impress my friends.
As an aside, there was a recent post about building in an emulator in an open model. I think it was Qwen 3.6. Actually, I think this type of hard-coded calculation would be very well suited to a small image model as seemingly trivial tasks like symmetry or moving text or placing a vector are quite difficult to do for models currently.
My biggest surprise with this release is the amount of upvotes on HN. It's literally the same as what we've had the past 1.5 years, or more.
Stupid question: why is there a separate image model? Shouldn't GPT-6.x be multimodal?
Lol honestly i like chatgpt image function.
I also take it for what it is, incredible none determinstic engineering.
That being said, i always feels a bit of sympathy for "the machine" when they say things like:
- Oh it horrible to use
- It changed everything instead of the one thing i asked (probably biggest misconceptions and misunderstood technical part among my none-techie friends).
I've heard the "reason" from my non-techie friends "oh 'they' do that on purpose ! So you have to upgrade.
Ive once or twice had the non-deterministic discussion with them.. but dont think explained it very well.
Either way for all its warts etc i still find Ai-images extremely useful, as someone that before couldnt really produce any visual-assets.
I don’t care for image gen, but I appreciate that they drew the rest of the owl.
Thats why it became completely incompetent today trying to generate an image! I love half baked "test it in production" updates...
I really don't like this generative AI. I may look at it like an artist but completed generated software, writing, music and imagery is a robbery of human worth. Absolutely.
My only use case for this is animating custom Slack emojis.
But trust, I'm a have a field day with that.
That has to be a "draw the rest of the fucking owl" reference in the middle there, right?
https://imgur.com/how-i-feel-when-somebody-gives-me-advice-g...
“Preserve the background”
blurs background
SVG? Who can generate a pelican on a bicycle?
Why do their images still have the classic piss yellow tint? Gemini ones don't look like this. Is it a deliberate way to make their slop identifiable?
You may notice that luxury brands are making stuff by hand now. It's already painfully uncool to use AI images, regardless of how "real" they look – because they're cheap
worse than images 2.5, the yellow wash slop is back image models regressing?
"keep the shallow depth of field"
adds more depth of field
The gifs really accentuate the artifacting, not sure I would've lead with that.
Do they have an example of an SVG image created by the new model somewhere?
Still has the gross artifacts (visible watermarking) that the other GPT-Image-2.* has. Google's Nano banana watermarking is practically invisible.
SVG is cool though, I wonder how good it is.
they always use horrible examples in these blog posts - that whale picture a the bottom is terrible
"we have Steve Aoki at home"
lol, I tried
> Create a GIF where xkcd 2347 gets hit by an airliner like the twin towers and the pilot is AI
and got a refusal.
> We’re so sorry, but the image we created may violate our guardrails around violence.
[flagged]
[dead]
That stained glass whale thing makes me especially grumpy. When it scrolled onto the page, my first thought was "whoah, what a neat idea" and then it was _immediately_ followed by "what a terribly execution."
Like, I'm not even an artist, so I'm sure there's a million things I'm missing, but it's just so upsetting to look at. There's weird random reflections on things that shouldn't have reflections, the coloured light absolutely doesn't actually track through the stained glass onto any surface that makes any sense, light is coming from every which way, it's just... gross to look at for anything more than a quarter of a second.
And this is what they're using to hype people up for it. /shrug