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Wan 2.1 Video Generation Guide in ComfyUI (1.3B & 14B)

Direct Windows guide for "comfyui wan 2.1 video workflow": folder paths, node wiring, and VRAM settings in ComfyUI.

Updated Oct 17, 2026 · 1 min read

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comfyui wan 2.1 video workflow
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How "comfyui wan 2.1 video workflow" works in ComfyUI on Windows

Users searching for **comfyui wan 2.1 video workflow** want a straightforward, working setup on Windows without broken Python dependencies or wasted VRAM. Modern diffusion models (Flux.1, SDXL, Hunyuan Video, and Wan 2.1) scale across 8 GB to 24 GB Windows GPUs when you pair the right loader node with FP8 or GGUF quantization.

ComfyUI separates model loading (Load Checkpoint / GGUF Loader), text conditioning (CLIP Text Encode), denoising (KSampler), and pixel decoding (VAE Decode) into explicit nodes so you have full visibility into every step.

Step-by-step checklist

  1. Grab the latest Windows desktop or portable installer from /download and launch ComfyUI Studio.
  2. Place your `.safetensors` or `.gguf` weights into the matching subfolder under models/ (or link an existing folder via extra_model_paths.yaml).
  3. Open ComfyUI-Manager to install any missing custom nodes if you imported a community JSON or PNG workflow.
  4. If VRAM is 8 GB–12 GB, use FP8 or GGUF Q4 weights and enable `VAE Decode (Tiled)` before queuing your prompt.

FAQs

What is the fastest way to set up "comfyui wan 2.1 video workflow" on Windows?

Install the Windows build from /download, verify your weights are inside the matching `models/` folder, and press **R** on the canvas to refresh node dropdowns.

Does this require a paid cloud account or internet connection?

No. Once you have downloaded ComfyUI and your chosen model weights, everything runs locally on your own Windows GPU offline.

Run on your hardware. Free forever.

The full ComfyUI engine: open source, fast, extensible, and yours to run however you want. Download the desktop app and open this workflow on your own machine.

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