Setup Wan_2.2_ComfyUI_Repackaged Locally via LM Studio with Native FP4

Setup Wan_2.2_ComfyUI_Repackaged Locally via LM Studio with Native FP4

Deploying this model locally is quickest when done via Docker.

Please follow the instructions listed below to get started.

During setup, the script automatically determines and applies the best settings tailored to your machine.

💾 File hash: caed1d18634ee89c9bcfb5f9d8f23ab4 (Update date: 2026-06-25)



  • Processor: Intel i7 / Ryzen 7 for heavy Quantized models
  • RAM: 48 GB needed to prevent memory swapping to disk
  • Disk: 150+ GB for high-context vector database storage
  • 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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