Nunchaku's SVDQuant 4-bit quantization method (W4A4) is now natively integrated into Hugging Face Diffusers via a new 'Nunchaku Lite' path. Pre-quantized checkpoints load with a standard `from_pretrained()` call — no local CUDA compilation needed, as kernels are fetched from the Hub via the `kernels` package. Nunchaku Lite patches `nn.Linear` modules with SVDQ W4A4 and AWQ W4A16 runtime layers, delivering ~30% speedup and up to 50% VRAM reduction vs BF16 baselines. Combined with `torch.compile`, speedup reaches 1.8x. NVFP4 precision requires Blackwell GPUs (RTX 50 series), while INT4 works on Turing/Ampere/Ada. The companion `diffuse-compressor` toolkit lets users quantize new architectures, package them as standard Diffusers repos, and publish to the Hub. A detailed walkthrough covers inspecting, calibrating, quantizing, packaging, and verifying a model (FLUX.2 Klein 4B as example), including handling structural rewrites like fused QKV projections.
