Nunchaku brings 4-bit diffusion to Diffusers

Hugging Face's Diffusers blog describes Nunchaku integration for 4-bit diffusion-transformer inference, aimed at reducing the VRAM needed for large image models. Why it matters: Local image workflows are often blocked by memory before model quality. Quantized diffusion inference can move experiments from rented high-memory GPUs onto more reachable hardware.

Try this: If an image workflow is VRAM-bound, test one Diffusers pipeline with Nunchaku and compare memory use, generation time, and visible artifacts before changing the default stack.