direct pdf https://deploymentsafety.openai.com/chatgpt-images-2-0/chatg...
I know this is probably mega cherry-picked to look more impressive, but some of the images are terrifyingly realistic. They seem to have put a lot of effort into the lighting.
Seeing is not believing anymore, and I don't think SynthID or anything like it can restore that trust in images.
From the system card someone linked elsewhere in the discussion
GPT Image 2
Low : 1024×1024 $0.006 | 1024×1536 $0.005 | 1536×1024 $0.005
Medium : 1024×1024 $0.053 | 1024×1536 $0.041 | 1536×1024 $0.041
High : 1024×1024 $0.211 | 1024×1536 $0.165 | 1536×1024 $0.165
Low : 1024×1024 $0.011 | 1024×1536 $0.016 | 1536×1024 $0.016
Medium : 1024×1024 $0.042 | 1024×1536 $0.063 | 1536×1024 $0.063
High : 1024×1024 $0.167 | 1024×1536 $0.25 | 1536×1024 $0.25Consistency? So it fails less often?
Based on the released images, (especially the one "screenshot" of the Mac desktop) I feel like the best images from this model are so visually flawless that the only way to tell they're fake is by reasoning about the content of the image itself (ex. "Apple never made a red iPhone 15, so this image is probably fake" or "Costco prices never end in .96 so this image is probably fake")
Especially when it comes to detailed outputs or non-standard prompts.
I do believe it will get even better - not sure it will happen within a year but I wouldn't be incredibly surprised if it did.
I experimented with the concept of procedural generation of Waldo-style scavenger images with Flux models with rather disappointing results. (unsurprisingly).
I would imagine this will hit illustrators / graphics designers / similar people very hard, now that anyone can just generate professional looking graphical content for pennies on the dollar.
As with anything AI, we are not ready for the scale of impact. And for what? Like, why are you proud of this?
That being said, gpt-image-1.5 was a big leap in visual quality for OpenAI and eliminated most of the classic issues of its predecessor, including things like the “piss filter.”
I’ll update this comment once I’ve finished running gpt-image-2 through both the generative and editing comparison charts on GenAI Showdown.
Since the advent of NB, I’ve had to ratchet up the difficulty of the prompts especially in the text-to-image section. The best models now score around 70%, successfully completing 11 out of 15 prompts.
For reference, here’s a comparison of ByteDance, Google, and OpenAI on editing performance:
https://genai-showdown.specr.net/image-editing?models=nbp3,s...
And here’s the same comparison for generative performance:
https://genai-showdown.specr.net/?models=s4,nbp3,g15
UPDATE: gpt-image-2 has already managed to overcome one of the so‑called “model killers” on the test suite: the nine-pointed star.
minimaxir•1h ago
API Pricing is mostly unchanged from gpt-image-1.5, the output price is slightly lower: https://developers.openai.com/api/docs/pricing
...buuuuuuuuut the price per image has changed. For a high quality image generation the 1024x1024 price has increased? That doesn't make sense that a 1024x1024 is cheaper than a 1024x1536, so assuming a typo: https://developers.openai.com/api/docs/guides/image-generati...
The submitted page is annoyingly uninformative, but from the livestream it proports the same exact features as Gemini's Nano Banana Pro. I'll run it through my tests once I figure out how to access it.
strongpigeon•23m ago
I think you meant more expensive, right? Because it would make sense for it to be cheaper as there are less pixels.