These models are the result of a partial NVFP4 quantization of <a target="_blank" rel="ugc" href="https://huggingface.co/lightx2v/Wan2.2-I2V-A14B-Moe-Distill-Lightx2v">Wan2.2-I2V-A14B-Moe-Distill-Lightx2v</a><a target="_blank" rel="ugc" href="https://huggingface.co/lightx2v/Wan2.1-I2V-14B-480P-StepDistill-CfgDistill-Lightx2v"> </a>by lightx2v, produced using <a target="_blank" rel="ugc" href="https://github.com/silveroxides/convert_to_quant">convert_to_quant</a> by <a target="_blank" rel="ugc" href="https://huggingface.co/silveroxides">silveroxides</a>. Some layers have been kept on their original BF16 format, while others were quantized as MXFP8 or NVFP4, mostly.<a target="_blank" rel="ugc" href="https://huggingface.co/lightx2v/Wan2.2-I2V-A14B-Moe-Distill-Lightx2v">Wan2.2-I2V-A14B-Moe-Distill-Lightx2v</a> is an image-to-video generation model built on <a target="_blank" rel="ugc" href="https://huggingface.co/Wan-AI/Wan2.2-I2V-A14B">Wan2.2-I2V-A14B</a>. It applies step distillation and a MoE architecture to reduce inference to 4 steps without CFG, cutting generation time substantially while preserving output quality. IMPORTANTSince NVFP4 is only supported on NVIDIA Blackwell architecture GPUs, running this model requires a Blackwell GPU with its corresponding support enabled in torch, along with a recent version of ComfyUI and <a target="_blank" rel="ugc" href="https://github.com/Comfy-Org/comfy-kitchen">comfy-kitchen</a> built against CUDA 13.

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