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Comment by anjneymidha | Hacker News Reader

Technical report here for those curious: https://cdn.sanity.io/files/gsvmb6gz/production/880b07220899...

Seems implementation is straightforward (very similar to everyone else, HiDream-E1, ICEdit, DreamO etc.), the magic is on data curation (which details are lightly shared).

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?

Diffusion based. There is no point to move to auto-regressive if you are not also training a multimodality LLM, which these companies are not doing that.

Well it's a "generative flow matching model"

That's not the same as a diffusion model.

Here is a post about the difference that seems right at first glance: https://diffusionflow.github.io/

Unfortunately, nobody wants to read the report, but what they are really after is to download the open-weight model.

So they can take it and run with it. (No contributing back either).

"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

Distilled is a real downer, but I guess those AI startup CEOs still gotta eat.

The open community has a done a lot with the open-weights distilled models from Black Forest Labs already, one of the more radical being Chroma: https://huggingface.co/lodestones/Chroma

I don't doubt that people can do nice things with them. But imagine what they could do with the actual model.

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"

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