Wan Video 2.1

    wanVideo_clipVisionH.safetensors Checkpoint / Wan Video

    Model Information
    Model Name
    Wan Video 2.1
    Version
    Clip Vision h
    Size
    1.18 GB
    Downloads
    240
    Torrent Details
    BTIH
    8469016FF3537E57D0993A55138861B0628B65FE
    BTMH
    56488FD2CBEA0BB9BA71074D74DCD2BE47EFEB8A8DCD3E792F4D0311C3072A58
    SHA256
    64A7EF761BFCCBADBAA3DA77366AAC4185A6C58FA5DE5F589B42A65BCC21F161
    Upload Date
    12 months ago
    Uploader
    CivitasBay.org
    Status
    10 Seeders
    1 Peers
    Info

    This model is the result of a partial NVFP4 quantization of Wan2.1-I2V-14B-480P-StepDistill-CfgDistill-Lightx2v by lightx2v, produced using convert_to_quant by silveroxides. Some layers have been kept on their original BF16 format, while others were quantized as MXFP8 or NVFP4, mostly.

    Wan2.1-I2V-14B-480P-StepDistill-CfgDistill-Lightx2v is an image-to-video generation model built on Wan2.1-I2V-14B-480P. It applies step distillation and classifier-free guidance distillation to reduce inference to 4 steps without CFG, cutting generation time substantially while preserving output quality.

    IMPORTANT

    Since 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 comfy-kitchen built against CUDA 13. You'll also need at least torch 2.10 to make it run, so this is not for the faint of heart with all the corresponding, if you know what I mean.

    The model can be used in ComfyUI with the following parameters, based on the distilled model's own recommendations:

    • Shift: 5.0

    • Sampler/Scheduler: euler/simple

    • CFG: 1.0

    • Steps: 4

    Other combinations are possible, such as lcm, heun/linear_quadratic, etc.

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