— Image Generation Tool

Qwen Image Edit

Last updated 2026-08-04 · Reviewed by ToolForge Editorial

Open-source image editing powered by Alibaba's Qwen-VL family

★ 4.3 · Open source (1M+ model downloads in first month) · Since 2025 (Alibaba Qwen team) · Yes — fully open source

$0 Free and open source (Apache 2.0); hosted from ~$0.003/img on Replicate

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Instruct-based photo edits that understand text

Qwen Image Edit is the editing variant of Alibaba's Qwen-Image family. It follows natural-language instructions ("change the jacket to red", "remove the watermark, keep the person") while preserving everything else with high fidelity. The 20B-parameter model runs locally on a single consumer GPU, is released under Apache 2.0, and is the strongest open instruct-image-editing model currently available.

Who it's for: Developers, agencies, and creators who want per-image editing without per-seat SaaS pricing or sending data to a closed API.

Key features

Wand Instruct-based editing

Describe the edit in plain English rather than masking regions manually; the model infers the target from context.

Shield Structure preservation

Background, lighting, and non-edited regions survive the edit with minimal drift.

Cpu Runs locally

Apache 2.0 licensed — you can run it on a single RTX 4090 or 32GB+ datacenter GPU.

Languages Bilingual prompts

Trained on Chinese-English bilingual data for stronger cross-lingual instruction following.

The honest take

✓ What works

Fully open-source under Apache 2.0 (completely free for commercial use)
Instruct-edit paradigm eliminates most manual masking work
Preserves fine detail (faces, fabric, logos) better than Flux Kontext LoRAs
Active community integrations (ComfyUI, diffusers, AUTOMATIC1111)

✗ What doesn't

Requires a 24GB+ VRAM GPU to run locally at practical speeds
No first-party hosted UI; you need ComfyUI or a hosted provider like Replicate
Complex compositional edits sometimes require 2-3 passes
Video editing not supported — images only

Verdict

The open-source answer to Flux Kontext — same paradigm, no license fee.

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