Wan_2.2_ComfyUI_Repackaged on AMD/Nvidia GPU with Native FP4

Wan_2.2_ComfyUI_Repackaged on AMD/Nvidia GPU with Native FP4

Wan_2.2_ComfyUI_Repackaged on AMD/Nvidia GPU with Native FP4

The shortest path to running this model is by activating Hyper-V features.

Make sure you implement the steps mentioned below.

The setup auto-downloads all needed files (several GBs).

To guarantee smooth performance, the process auto-selects the best options.

📘 Build Hash: 0098fbe7e2974c876333b02674b70681 • 🗓 2026-07-03



  • CPU: modern architecture (Zen 3 / Alder Lake minimum)
  • RAM: 64 GB to avoid OOM crashes on large contexts
  • Disk Space: 80 GB NVMe SSD required for fast model weights loading
  • GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats

The Wan_2.2_ComfyUI_Repackaged model delivers state‑of‑the‑art text‑to‑image generation with unprecedented speed and quality. Built on the ComfyUI framework, it seamlessly integrates into existing workflows, allowing artists and developers to iterate rapidly. Its architecture supports a wide range of aspect ratios and can produce images up to 4096×4096 pixels, making it ideal for both concept art and detailed illustration. A key advantage is the model’s efficient memory footprint, enabling high‑performance inference on consumer‑grade GPUs without sacrificing detail. Below is a quick comparison of its core specifications:

Parameter Value
Model Type Text‑to‑Image
Parameter Count 2.5 B
Max Resolution 4096×4096
Framework ComfyUI

Users have reported impressive results in both speed and visual fidelity, cementing its position as a go‑to tool for modern creative pipelines.

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