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WanVideoModelLoaderMultiGPU.md

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WanVideoModelLoaderMultiGPU

WanVideoModelLoaderMultiGPU wraps the base WanVideo model loader so you can pick both the loader device and the downstream compute device when working with large WanVideo checkpoints. The node patches the underlying WanVideo loader so the model materialises on the device chosen via compute_device while still honouring WanVideo's block swap and quantisation options.

Inputs

Required

Parameter Data Type Description
model STRING Model file from ComfyUI/models/diffusion_models or ComfyUI/models/unet_gguf to load.
base_precision STRING Floating-point format for base weights (fp32, bf16, fp16, or fp16_fast).
quantization STRING Optional FP8 quantisation preset; disabled keeps original precision.
load_device STRING WanVideo loader slot (main_device or offload_device) used during initial weight materialisation.
compute_device STRING MultiGPU device id (e.g. cuda:0, cuda:1, cpu) to run inference on.

Optional

Parameter Data Type Description
attention_mode STRING Select specialised attention kernels (sdpa, flash_attn_2, flash_attn_3, sageattn, sageattn_3, radial_sage_attention).
compile_args WANCOMPILEARGS Torch compile configuration passed through to WanVideo.
block_swap_args BLOCKSWAPARGS Enables WanVideo block swapping; supply alongside WanVideoBlockSwapMultiGPU.
lora WANVIDLORA Optional Wan LoRA bundle to apply during load.
vram_management_args VRAM_MANAGEMENTARGS DiffSynth-Studio memory manager arguments for aggressive VRAM reclamation.
extra_model VACEPATH Adds auxiliary model weights (e.g. VACE / MTV Crafter).
fantasytalking_model FANTASYTALKINGMODEL Preloads FantasyTalking speech model.
multitalk_model MULTITALKMODEL Preloads MultiTalk model.
fantasyportrait_model FANTASYPORTRAITMODEL Preloads FantasyPortrait model.
rms_norm_function STRING Choose RMSNorm implementation (default Wan variant or pytorch).

Outputs

Output Name Data Type Description
model WANVIDEOMODEL Initialised Wan diffusion model ready for sampling.
compute_device MULTIGPUDEVICE Device id chosen for downstream nodes; pass directly into samplers.