Qwen-Image-Edit_ComfyUI Using Pinokio Easy Build

The fastest tactical way to launch this model locally is via a Docker image.

Refer to the instructions below to proceed.

The installer automatically pulls the model (could be multiple GBs).

The automated script takes care of everything, tailoring the setup to your specs.

🔒 Hash checksum: 123ee4d977bb5ec745ddadecbd236853 • 📆 Last updated: 2026-06-24



  • CPU: modern architecture (Zen 3 / Alder Lake minimum)
  • RAM: fast 5600MHz+ required to avoid memory bottlenecks
  • Disk Space: 100 GB for multi-modal model vision components
  • Graphics: TensorRT-LLM / vLLM inference engine compatible chip

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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