Ce qui s'est passé: Bringing Nunchaku 4-bit Diffusion Inference to Diffusers

Hugging Face integrated Nunchaku 4-bit quantization into Diffusers, enabling diffusion models to run with 4-bit weights and activations for faster inference and lower memory.

Pourquoi ça compte: Bringing Nunchaku 4-bit Diffusion Inference to Diffusers

Engineers deploying text-to-image models on consumer GPUs need to reduce VRAM from 20-30GB to fit models like ERNIE or FLUX on hardware with limited memory.

Dans l'actualité

Bringing Nunchaku 4-bit Diffusion Inference to Diffusers

Hugging Face · Publié le 23 juillet 2026 · 3 min de lecture

En 30 secondes

Ce qui s'est passé: Hugging Face integrated Nunchaku 4-bit quantization into Diffusers, enabling diffusion models to run with 4-bit weights and activations for faster inference and lower memory.
Pourquoi ça compte: Engineers deploying text-to-image models on consumer GPUs need to reduce VRAM from 20-30GB to fit models like ERNIE or FLUX on hardware with limited memory.
Vigilance: NVFP4 kernels require NVIDIA Blackwell GPUs; earlier generations must use INT4 variants. Speedup is about 30 percent, less than the original Nunchaku engine's model-specific optimizations.

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