gpt-image-1 (aka "4o") is still the most useful general purpose image model, but damn does this come close.

I'm deep in this space and feel really good about FLUX.1 Kontext. It fills a much-needed gap, and it makes sure that OpenAI / Google aren't the runaway victors of images and video.

Prior to gpt-image-1, the biggest problems in images were:

  - prompt adherence
  - generation quality
  - instructiveness (eg. "put the sign above the second door")
  - consistency of styles, characters, settings, etc. 
  - deliberate and exact intentional posing of characters and set pieces
  - compositing different images or layers together
  - relighting

OpenAI's gpt-image-1 solved all of these things with a single multimodal model. You could throw out ComfyUI and all the other pre-AI garbage and work directly with the model itself. It was magic.

Unfortunately, gpt-image-1 is ridiculously slow, insanely expensive, highly censored (you can't use a lot of copyrighted characters or celebrities, and a lot of totally SFW prompts are blocked). It can't be fine tuned, so you're suck with the "ChatGPT style" and (as is called by the community) the "piss filter" (perpetually yellowish images).

And the biggest problem with gpt-image-1 is because it puts image and text tokens in the same space to manipulate, it can't retain the exact precise pixel-precise structure of reference images. Because of that, it cannot function as an inpainting/outpainting model whatsoever. You can't use it to edit existing images if the original image mattered.

Even with those flaws, gpt-image-1 was a million times better than Flux, ComfyUI, and all the other ball of wax hacks we've built up. Given the expense of training gpt-image-1, I was worried that nobody else would be able to afford to train the competition and that OpenAI would win the space forever. We'd be left with only hyperscalers of AI building these models. And it would suck if Google and OpenAI were the only providers of tools for artists.

Black Forest Labs just proved that wrong in a big way! While this model doesn't do everything as well as gpt-image-1, it's within the same order of magnitude. And it's ridiculously fast (10x faster) and cheap (10x cheaper).

Kontext isn't as instructive as gpt-image-1. You can't give it multiple pictures and ask it to copy characters from one image into the pose of another image. You can't have it follow complex compositing requests. But it's close, and that makes it immediately useful. It fills a much-needed gap in the space.

Black Forest Labs did the right thing by developing this instead of a video model. We need much more innovation in the image model space, and we need more gaps to be filled:

  - Fast
  - Truly multimodal like gpt-image-1
  - Instructive 
  - Posing built into the model. No ControlNet hacks. 
  - References built into the model. No IPAdapter, no required character/style LoRAs, etc. 
  - Ability to address objects, characters, mannequins, etc. for deletion / insertion. 
  - Ability to pull sources from across multiple images with or without "innovation" / change to their pixels.
  - Fine-tunable (so we can get higher quality and precision) 
 

Please build it, Black Forest Labs.

All of those feature requests stated, Kontext is a great model. I'm going to be learning it over the next weeks.

Keep at it, BFL. Don't let OpenAI win. This model rocks.

Now let's hope Kling or Runway (or, better, someone who does open weights -- BFL!) develops a Veo 3 competitor.

I need my AI actors to "Meisner", and so far only Veo 3 comes close.

anything is more accurate than the llms at generating images. chatgpt, google gemini, all of them... they're not optimized for image generation. it's why veo is an entirely different model from google for example. and even veo isn't the best video model either. people dedicated to images and video are just spending more time here (such as black forest labs). as a result, those specialized models are better.