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FLUX.2: Frontier Visual Intelligence

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Re: FLUX.2: Frontier Visual Intelligence

#51

Post by qoez »

andersa wrote: post #44
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.

Makes no sense since they should have checkpoints earlier in the run that they could restart from and they should have regular checks that keep track if a model has exploded etc.

Re: FLUX.2: Frontier Visual Intelligence

#52

Post by 85392_school »

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…

FYI: photorealism is art that imitates photos, and I see the term misused a lot both in comments and prompts (where you'll actually get subideal results if you say "photorealism" instead of describing the camera that "shot" it!)

Re: FLUX.2: Frontier Visual Intelligence

#53

Post by embedding-shape »

qoez wrote: post #51
andersa wrote: post #44

Earlier quoted context omitted.

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

Makes no sense since they should have checkpoints earlier in the run that they could restart from and they should have regular checks that keep track if a model has exploded etc.

I didn't read "major failed training run" as in "the process crashed and we lost all data" but more like "After spending N weeks on training, we still didn't achieve our target(s)", which could be considered "failing" as well.

Re: FLUX.2: Frontier Visual Intelligence

#54

Post by [deleted] »

542458 wrote: post #5

> Run FLUX.2 [dev] on GeForce RTX GPUs for local experimentation with an optimized fp8 reference implementation of FLUX.2 [dev], created in collaboration with NVIDIA and ComfyUI. Glad to see that they're sticking with open weights. That said, Flux 1.x was 12B params, right? So this is about 3x as large plus a 24B text encoder (unless I'm misunderstanding), so it might be a significant challenge for local use. I'll be…

[deleted]

Re: FLUX.2: Frontier Visual Intelligence

#56

Post by babaganoosh89 »

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…

Flux 2 Dev is not IP censored

Re: FLUX.2: Frontier Visual Intelligence

#57

Post by vunderba »

minimaxir wrote: post #47
vunderba wrote: post #45

Earlier quoted context omitted.

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.

Agreed - I was quite surprised. Even though its a bog-standard 1024x1024 image, the somewhat low quality nature of a TV still provides for an interesting challenge. All the BFL models (Kontext Max and Flux 2 Pro) seemed to struggle hard with it.

Re: FLUX.2: Frontier Visual Intelligence

#58

Post by Yokohiii »

AmazingTurtle wrote: post #16

I ran "family guy themed cyberpunk 2077 ingame screenshot, peter griffin as main character, third person view, view of character from the back" on both nano banana pro and bfl flux 2 pro. The results were staggering. The google model aligned better with the cyberpunk ingame scene, flux was too "realistic"

i think they focus their dataset on photography. flux 1 dev one was never really great at artistic style, mostly locking you into a somewhat generic style. my little flux 2 pro testing does seem to verify that. but with lora ecosystem and enough time to fiddle flux 1 dev is probably still the best if you want creative stylistic results.

Re: FLUX.2: Frontier Visual Intelligence

#59

Post by cubefox »

85392_school wrote: post #52
cubefox wrote: post #46

Earlier quoted context omitted.

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…

FYI: photorealism is art that imitates photos, and I see the term misused a lot both in comments and prompts (where you'll actually get subideal results if you say "photorealism" instead of describing the camera that "shot" it!)

I meant it here in the sense of "as indistinguishable from a photo as the model can make it".

Re: FLUX.2: Frontier Visual Intelligence

#60

Post by crest »

minimaxir wrote: post #12
542458 wrote: post #5

> Run FLUX.2 [dev] on GeForce RTX GPUs for local experimentation with an optimized fp8 reference implementation of FLUX.2 [dev], created in collaboration with NVIDIA and ComfyUI. Glad to see that they're sticking with open weights. That said, Flux 1.x was 12B params, right? So this is about 3x as large plus a 24B text encoder (unless I'm misunderstanding), so it might be a significant challenge for local use. I'll be…

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.

The download is a trivial onetime cost and so is storing it on a direct attached NVMe SSD. The expensive part is getting a GPU with 64GB of memory.
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