FLUX.1 Kontext

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.

I have no affiliation with either company but from using both a bunch as a customer: Replicate has a competitor at https://fal.ai/models and FAL's generation speed is consistently faster across every model I've tried. They have some sub-100 ms image gen models, too.

Replicate has a much bigger model selection. But for every model that's on both, FAL is pretty much "Replicate but faster". I believe pricing is pretty similar.

That's less on the downstream distributors, more on the model developers themselves realizing that ease-of-accessibility of the models themselves on Day 1 is important for getting community traction. Locking the model exclusively behind their own API won't work anymore.

Llama 4 was another recent case where they explicitly worked with downstream distributors to get it working Day 1.

The open weights variant is "coming soon" so the only option is hosted right now.

It is through Replicate's UI listed, which goes through Black Forest Labs's infra so would likely get the same results from their API.

I tried making a realistic image from a cartoon character but aged. It did very well, definitely recognisable as the same 'person'.

I haven't been following image generation models closely, at a high level is this new Flux model still diffusion based, or have they moved to block autoregressive (possibly with diffusion for upscaling) similar to 4o?

"FLUX.1 Kontext [dev]

Open-weights, distilled variant of Kontext, our most advanced generative image editing model. Coming soon" is what they say on https://bfl.ai/models/flux-kontext

I agree that gooning crew drives a lot of open model downloads.

On HN, generally, people are more into technical discussion and/or productizing this stuff. Here, it seems declasse to mention the gooner angle, it's usually euphemized as intense reactions about refusing to download it involving the words "censor"

Damn, I’m just too lazy to learn skills that will be outdated in 6 months

Well thank you I will test that

Even using WSL2 with Ubuntu isn't good enough ?

I get that but usually you would have two inputs, the reference “true”, and the target that it to be manipulated.

> They chosen Asian traits that Western beauty standards fetishize that in Asia wouldn't be taken serious at all.

> where as Chinese text2image generate attractive and more light skinned humans.

Are you saying they have chosen Asian traits that Asian beauty standards fetishize that in the West wouldn't be taken seriously at all? ;) There is no ground truth here that would be more correct one way or the other.

> notice American text2image models tend to generate less attractive and more darker skinned humans where as Chinese text2image generate attractive and more light skinned humans

This seems entirely subjective to me.

Wow, that is some straight-up overt racism. You should be ashamed.

Your generated examples just look like generic modern-day mechanical keyboards, they don't have any of the Model Fs defining features.

Your Google Images search indicates the original problem of models training on junk misinformation online. If AI scrapers are downloading every photo that's associated with "Model F Keyboard" like that, the models have no idea what is an IBM Model F, or its distinguishing characteristics, and what is some other company's, and what is misidentified.

https://commons.wikimedia.org/wiki/Category:IBM_Model_F_Keyb...

Specifying "IBM Model F keyboard" and placing it in quotation marks improves the search. But the front page of the search is tip-of-the-iceberg compared to whatever the model's scrapers ingested.

Eventually you may hit trademark protections. Reproducing a brand-name keyboard may be as difficult as simulating a celebrity's likeness.

I'm not even sure what my friends look like on Facebook, so it's not clear how an AI model would reproduce a brand-name keyboard design on request.