Wan_2.2_ComfyUI_Repackaged Locally (No Cloud) One-Click Setup Windows

If you want the fastest local installation for this model, use standard pip packages.

Kindly follow the on-screen instructions below.

Hands-free setup: the system self-downloads the heavy model files.

During setup, the script automatically determines and applies the best settings.

💾 File hash: 8f3cdf9110ec578f81ac8835e7487c5c (Update date: 2026-06-23) Verify CPU: 8-core / 16-thread recommended for orchestration RAM: 48 GB needed to prevent memory swapping to disk Storage:100 GB free space for HuggingFace cache folder 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:

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

1. Installer setting up SillyTavern interface optimized for KoboldCPP 1.80+
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3. Downloader pulling advanced upscaler model weights like SUPIR-v2 for custom WebUI engines
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5. Downloader for specialized TabbyML code-completion model backends
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7. Setup tool configuring MemGPT agent memory layers with local GGUF nodes
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9. Downloader pulling optimized Flux.1-Dev safetensors for local UIs
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11. Installer deploying automated RAG data chunking pipelines for multi-format text catalogs assets
12. Wan_2.2_ComfyUI_Repackaged Quantized GGUF