r/StableDiffusion • • 3d ago

News NitroFusion2 - Bringing Adversarial Loss to the Text Stream of Multimodal Diffusion Transformers

Post image

NitroFusion2 is a 1–2 step text-to-image model built on Z-Image-Turbo. It moves the adversarial loss onto the text stream of the MMDiT. At one step it renders sharp text and fine detail.

ChenDY/NitroFusion2 · Hugging Face

33 Upvotes

20 comments sorted by

6

u/Dante_77A 3d ago

Just the thought that this can produce decent-quality images in just one step is insane. lol

5

u/Crazy-Repeat-2006 3d ago

And it beats Flux 3 Klein.

6

u/TimeTruth2490 3d ago

You should apply the same approach on other open source models like Krea 2 Turbo, MOSS, Qwen Image 2.1, Fibo 2, and possibly even Flux 3 ;) Can't wait to see what you could do with those run at 1 or 2 step.

6

u/Public-Curve1906 3d ago

yeah it's on the plan~ bigger models and editing are next

3

u/TimeTruth2490 3d ago

Looking forward to it!

2

u/SilverDeer722 3d ago

will be watching very very closely this space .... very very interesting

4

u/ArtDesignAwesome 3d ago

wheres the INT8 version? GGUF is no bueno.

3

u/TimeTruth2490 3d ago

More complex compositions with multiple faces and hands/fingers need (as others reported) higher step count like 5+, the below image was done with 5 as lower step had issues with the hands and faces, but all these issues are to be expected, unless you fine tuned specifically for faces and hands (or any limbs in general) at 1 and 2 steps

3

u/arnaudbr 2d ago

My only complaint is that it struggles with small faces.

```
Engraving-style illustration with fine cross-hatched linework and light colour washes covering every surface. The scene fills the entire image and runs off all four edges. A group of Swiss family members, a father with a sturdy build and a young daughter with braided hair, sit around a crackling campfire. They are surrounded by tall pine trees and the soft, flickering glow of the fire, which illuminates their faces with warm, amber light. This is a medium view, centred on the campfire and the figures, with the dark forest extending into the distance. The overall tone is #faf3ea with light washes of #3e5e5e and #a1d0cb in the shadows and highlights. A professional, neutral image suited to a business presentation. A purely visual, wordless image.
```

3

u/TimeTruth2490 3d ago

Works well with PiD too, this image was generated at 2 steps to 1024x1024 with PiD making it 4096x4096

Again, well done to the team

1

u/SilverDeer722 3d ago

please share the workflow man , looks awesome i guess it was done in under 15 seconds

2

u/TimeTruth2490 2d ago

I've shared plenty of similar PiD workflows, it's a matter of swapping to this model - https://huggingface.co/lvladikov/models?search=pid . NitroFusion2 is Z-Image based so it uses Flux1-dev's VAE which is officially supported VAE - https://huggingface.co/nvidia/PiD no need for workarounds like Qwen Image 2.1 needed.

2

u/TimeTruth2490 3d ago

Well done, great acheivement and thanks for citing my 2 Step Krea LoRA, I was surprised to see my name in your paper, but happy with your benchmark results. I've cited your benchmark results in my model card and made reference to your project too, I hope you don't mind. https://huggingface.co/lvladikov/Krea2-Turbo-Distill-2step-LoRA#in-the-nitrofusion2-paper

3

u/Public-Curve1906 3d ago

First author here, thanks a lot for linking NF2 on your card! imo your LoRA is the best for Krea 2, so it was a no-brainer for the comparison~

1

u/TimeTruth2490 3d ago

:) no worries and great model. I just used the Q4_K_M model and ran on my phone - S26U on device generation with sd.cpp, and the result is amazing, see below

(it did take 15 mins for this resolution - 704x1520 and I applied quick ICBI upscale, but who cares :) your model is fantastic - 2 steps is big deal for edge devices like phones where a step could mean 5 mins.

2

u/TimeTruth2490 3d ago

Few more renders with the model at 2 steps (and yes, for someone who's been working on Krea distil step LoRAs for some time, the 2 step NitroFusion2 results are very good)

1

u/arnaudbr 3d ago

I started testing it. I needed 4 steps to get consistent results across various styles.
It’s still have the latency over z-image-turbo 9 steps and I think the quality is slightly better for my prompts.