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Install Qwen-Image-Edit_ComfyUI on AMD/Nvidia GPU with Native FP4 Offline Setup

Install Qwen-Image-Edit_ComfyUI on AMD/Nvidia GPU with Native FP4 Offline Setup

The fastest method for installing this model locally is by using Docker.

Follow the guidelines below to continue.

The setup auto-streams the model assets (expect a multi-GB download).

The deployment tool scans your environment and automatically chooses the ideal parameters for your OS.

🛡️ Checksum: 845fe3430421c04aded9f436677ae82e — ⏰ Updated on: 2026-06-25



  • CPU: modern architecture (Zen 3 / Alder Lake minimum)
  • RAM: 64 GB to avoid OOM crashes on large contexts
  • Storage:100 GB free space for HuggingFace cache folder
  • GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference

The Qwen-Image-Edit_ComfyUI model leverages a state‑of‑the‑art diffusion framework to deliver precise image editing capabilities directly within the ComfyUI environment. It supports high‑resolution outputs and enables operations such as object removal, inpainting, and style transfer with minimal latency. A conditional guidance mechanism ensures semantic consistency across edited regions, preserving the original context while applying modifications. The architecture employs a dual‑encoder design that combines a vision encoder for detailed feature extraction and a text encoder for contextual understanding. Users can integrate the model into existing node‑based workflows without extensive retraining, making advanced editing accessible to both developers and artists. Below is a quick comparison of key performance metrics that highlight its efficiency and quality relative to similar tools.

Metric Value
Resolution 2048×2048
Inference Time ~120ms
PSNR 38.5 dB
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