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FLUX.2: Frontier Visual Intelligence

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Re: FLUX.2: Frontier Visual Intelligence

#41

Post by minimaxir »

I just finished my Flux 2 testing (focusing on the Pro variant here: https://replicate.com/black-forest-labs/flux-2-pro). Overall, it's a tough sell to use Flux 2 over Nano Banana for the same use cases, but even if Nano Banana didn't exist it's only an iterative improvement over Flux 1.1 Pro.

Some notes:

- Running my nuanced Nano Banana prompts though Flux 2, Flux 2 definitely has better prompt adherence than Flux 1.1, but in all cases the image quality was worse/more obviously AI generated.

- The prompting guide for Flux 2 (https://docs.bfl.ai/guides/prompting_guide_flux2) encourages JSON prompting by default, which is new for an image generation model that has the text encoder to support it. It also encourages hex color prompting, which I've verified works.

- Prompt upsampling is an option, but it's one that's pushed in the documentation (https://github.com/black-forest-labs/flux2/blob/main/docs/fl...). This does allow the model to deductively reason, e.g. if asked to generate an image of a Fibonacci implementation in Python it will fail hilariously if prompt sampling is disabled, but get somewhere if it's enabled: https://x.com/minimaxir/status/1993361220595044793

- The Flux 2 API will flag anything tangently related to IP as sensentive even at its lowest sensitivity level, which is different from Flux 1.1 API. If you enable prompt upsampling, it won't get flagged, but the results are...unexpected. https://x.com/minimaxir/status/1993365968605864010

- Costwise and generation-speed-wise, Flux 2 Pro is on par with Nano Banana, and adding an image as an input pushes the cost of Flux 2 Pro higher than Nano Banana. The cost discrepancy increases if you try to utilize the advertised multi-image reference feature.

- Testing Flux 1.1 vs. Flux 2 generations does not result in objective winners, particularly around more abstract generations.

Re: FLUX.2: Frontier Visual Intelligence

#42

Post by [deleted] »

minimaxir wrote: post #41

I just finished my Flux 2 testing (focusing on the Pro variant here: https://replicate.com/black-forest-labs/flux-2-pro ). Overall, it's a tough sell to use Flux 2 over Nano Banana for the same use cases, but even if Nano Banana didn't exist it's only an iterative improvement over Flux 1.1 Pro. Some notes: - Running my nuanced Nano Banana prompts though Flux 2, Flux 2 definitely has better prompt adherence than Flux…

[deleted]

Re: FLUX.2: Frontier Visual Intelligence

#43

Post by vunderba »

Updating the GenAI comparison website is starting to feel a bit Sisyphean with all the new models coming out lately, but the results are in for the Flux 2 Pro Editing model!

https://genai-showdown.specr.net/image-editing

It scored slightly higher than BFL's Kontext model, coming in around the middle of the pack at 6 / 12 points.

I’ll also be introducing an additional numerical metric soon, so we can add more nuance to how we evaluate model quality as they continue to improve.

If you're solely interested in seeing how Flux 2 Pro stacks up against the Nano Banana Pro, and another Black Forest model (Kontext), see here:

https://genai-showdown.specr.net/image-editing?models=km,nbp...

Note: It should be called out that BFL seems to support a more formalized JSON structure for more granular edits so I'm wondering if accuracy would improve using it.

Re: FLUX.2: Frontier Visual Intelligence

#44

Post by andersa »

spyder wrote: post #18

Great, especially that they still have an open-weight variant of this new model too. But what happened to their work on their unreleased SOTA video model? did it stop being SOTA, others got ahead, and they folded the project, or what? YT video about it: https://youtu.be/svIHNnM1Pa0?t=208 They even removed the page of that: https://bfl.ai/up-next/

I heard a possibly unsubstantiated rumor that they had a major failed training run with the video model and canceled the project.

Re: FLUX.2: Frontier Visual Intelligence

#45

Post by vunderba »

minimaxir wrote: post #41

I just finished my Flux 2 testing (focusing on the Pro variant here: https://replicate.com/black-forest-labs/flux-2-pro ). Overall, it's a tough sell to use Flux 2 over Nano Banana for the same use cases, but even if Nano Banana didn't exist it's only an iterative improvement over Flux 1.1 Pro. Some notes: - Running my nuanced Nano Banana prompts though Flux 2, Flux 2 definitely has better prompt adherence than Flux…

I've re-run my benchmark with the Flux 2 Pro model and found that in some cases the higher resolution models (I believe Flux 2 Pro handles 4k) can actually backfire on some of the tests because it'll introduce the equivalent of an almost ESRGAN style upscale which may add in unwanted additional details. (See the Constanza test in particular).

https://genai-showdown.specr.net/image-editing

Re: FLUX.2: Frontier Visual Intelligence

#46

Post by cubefox »

echelon wrote: post #36
spyder wrote: post #18

Great, especially that they still have an open-weight variant of this new model too. But what happened to their work on their unreleased SOTA video model? did it stop being SOTA, others got ahead, and they folded the project, or what? YT video about it: https://youtu.be/svIHNnM1Pa0?t=208 They even removed the page of that: https://bfl.ai/up-next/

Image models are more fundamentally important at this stage than video models. Almost all of the control in image-to-video comes through an image. And image models still needs a lot of work and innovation. On a real physical movie set, think about all of the work that goes into setting the stage. The set dec, the makeup, the lighting, the framing, the blocking. All the work before calling "action". That's what image…

Hot take: text-to-image models should be biased toward photorealism. This is because if I type in "a cat playing piano", I want to see something that looks like a 100% real cat playing a 100% real piano. Because, unless specified otherwise, a "cat" is trivially something that looks like an actual cat. And a real cat looks photorealistic. Not like a painting, or cartoon, or 3D render, or some fake almost-realistic-but-cleary-wrong "AI style".

Re: FLUX.2: Frontier Visual Intelligence

#47

Post by minimaxir »

vunderba wrote: post #45
minimaxir wrote: post #41

I just finished my Flux 2 testing (focusing on the Pro variant here: https://replicate.com/black-forest-labs/flux-2-pro ). Overall, it's a tough sell to use Flux 2 over Nano Banana for the same use cases, but even if Nano Banana didn't exist it's only an iterative improvement over Flux 1.1 Pro. Some notes: - Running my nuanced Nano Banana prompts though Flux 2, Flux 2 definitely has better prompt adherence than Flux…

I've re-run my benchmark with the Flux 2 Pro model and found that in some cases the higher resolution models (I believe Flux 2 Pro handles 4k) can actually backfire on some of the tests because it'll introduce the equivalent of an almost ESRGAN style upscale which may add in unwanted additional details. ( See the Constanza test in particular ). https://genai-showdown.specr.net/image-editing

That Constanza test result is baffling.

Re: FLUX.2: Frontier Visual Intelligence

#49

Post by Sharlin »

_ache_ wrote: post #25
minimaxir wrote: post #12

Earlier quoted context omitted.

Looking at the file sizes on the open weights version ( https://huggingface.co/black-forest-labs/FLUX.2-dev/tree/mai... ), the 24B text encoder is 48GB, the generation model itself is 64GB, which roughly tracks with it being the 32B parameters mentioned. Downloading over 100GB of model weights is a tough sell for the local-only hobbyists.

Even a 5090 can handle that. You have to use multiple GPUs. So the only option will be [klein] on a single GPU... maybe? Since we don't have much information.

As far as I know, no open-weights image gen tech supports multi-GPU workflows except in the trivial sense that you can generate two images in parallel. The model either fits into the VRAM of a single card or it doesn’t. A 5ish-bit quantization of a 32Gw model would be usable by owners of 24GB cards, and very likely someone will create one.

Re: FLUX.2: Frontier Visual Intelligence

#50

Post by minimaxir »

cubefox wrote: post #46
echelon wrote: post #36

Earlier quoted context omitted.

Image models are more fundamentally important at this stage than video models. Almost all of the control in image-to-video comes through an image. And image models still needs a lot of work and innovation. On a real physical movie set, think about all of the work that goes into setting the stage. The set dec, the makeup, the lighting, the framing, the blocking. All the work before calling "action". That's what image…

Hot take: text-to-image models should be biased toward photorealism. This is because if I type in "a cat playing piano", I want to see something that looks like a 100% real cat playing a 100% real piano. Because, unless specified otherwise, a "cat" is trivially something that looks like an actual cat. And a real cat looks photorealistic. Not like a painting, or cartoon, or 3D render, or some fake almost-realistic-but…

As Midjourney has demonstrated, the median user of AI image generation wants those aesthetic dreamy images.
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