Qwen Image
Qwen-Image is a state-of-the-art image generation and editing model with exceptional text rendering capabilities, including complex Chinese character generation.
Qwen 
WaveSpeed Image generation and editing with precise text rendering
Qwen-Image is an image generation and editing model developed by Alibaba's Qwen team. It accepts text prompts and source images as input and supports both text-to-image generation and a wide range of image editing tasks, including style transfer, object addition and removal, background changes, and pose manipulation. The model uses a dual-encoding architecture that processes images through both Qwen2.5-VL for semantic understanding and a VAE encoder for visual fidelity, feeding into an MMDiT backbone.
What distinguishes Qwen-Image from many other generation models is its ability to render complex text accurately within images, including multi-line layouts and logographic scripts such as Chinese characters. This capability is built using a curriculum learning strategy that progressively scales from simple to complex text rendering tasks during training. The model has been evaluated on benchmarks covering image generation, image editing, and text rendering, including GenEval, DPG, GEdit, LongText-Bench, ChineseWord, and CVTG-2K. It is well-suited for workflows that require accurate in-image typography, multilingual text, or detailed image editing from a source image.
What Qwen Image supports
Text-to-Image Generation
Generates images from text prompts across a wide range of artistic styles, evaluated on benchmarks including GenEval and DPG.
Image Editing
Edits source images via a reference imageUrl input, supporting style transfer, background changes, object addition, removal, replacement, and pose manipulation.
Complex Text Rendering
Renders multi-line, paragraph-level, and logographic text (including Chinese characters) within generated images, benchmarked on LongText-Bench, ChineseWord, and CVTG-2K.
LoRA Support
Accepts LoRA adapters as an input parameter, allowing fine-tuned style or subject customization to be applied at inference time.
Seed Control
Accepts a numeric seed input to enable reproducible image outputs across generation runs.
Image Understanding Tasks
Supports detection, segmentation, depth estimation, novel view synthesis, and super resolution as part of its unified architecture.
Ready to build with Qwen Image?
Get Started FreeCommon questions about Qwen Image
What is the context window for Qwen-Image?
The model has a context window of 10,000 tokens, as listed in the model metadata.
What input types does Qwen-Image accept?
Qwen-Image accepts an image URL (source image), numeric parameters for dimensions or other settings, LoRA adapter configurations, and a seed value for reproducibility.
What makes Qwen-Image's text rendering distinct?
The model uses a curriculum learning strategy that trains progressively from simple to complex text tasks, enabling accurate rendering of multi-line text and logographic scripts like Chinese characters within generated images.
What benchmarks has Qwen-Image been evaluated on?
Qwen-Image has been evaluated on GenEval and DPG for image generation; GEdit, ImgEdit, and GSO for image editing; and LongText-Bench, ChineseWord, and CVTG-2K for text rendering.
What is the training data cutoff for Qwen-Image?
The model's training date is listed as August 2025 in the model metadata.
What people think about Qwen Image
Community reception for Qwen-Image has been notably positive, with users on r/StableDiffusion and r/LocalLLaMA praising its realism, text rendering accuracy, and unified generation and editing capabilities. A thread highlighting realism examples accumulated over 1,000 upvotes, and the release of version 2.0 generated significant discussion around its 7B parameter size and native 2K resolution support.
Some community members have raised questions about the availability of smaller or quantized variants, with users asking when a 7B version would be released. Content moderation behavior and NSFW output have also been discussed, and several threads reflect interest in running the model locally.
Qwen Image 2 is amazing, any idea when 7b is coming ?
Are we having another WAN moment with Qwen Image 2.0?
QWEN IMAGE EDIT 2511 can do (N)SFW by itself
Qwen-Image2512 is a severely underrated model (realism examples)
Qwen-Image-2.0 is out - 7B unified gen+edit model with native 2K and actual text rendering
Documentation & links
Parameters & options
Up to 3 LoRAs.
A specific value that is used to guide the 'randomness' of the generation.
Explore similar models
Qwen Z Image Turbo
Alibaba's Tongyi Lab Z-Image is a 6-billion-parameter image generation foundation model that delivers state-of-the-art visual quality and prompt coherence using an efficient single-stream diffusion transformer architecture.
Qwen Qwen 2 Pro
Alibaba's unified image generation and editing model that excels at accurate text rendering, native 2K resolution output, and ranks #1 on AI Arena's blind human evaluation leaderboard.
Qwen Qwen3 235B
Alibaba's updated 235B Mixture-of-Experts model delivering top-tier reasoning, coding, and long-context understanding while only activating 22B parameters at a time.
Black Forest Labs FLUX.1 [dev] LoRA
FLUX.1 [dev] with LoRA support for fast, high-quality, personalized image generation using pre-trained style adapters.
X.ai Grok Imagine Pro
xAI's premium image generation model, delivering higher-quality visuals than the standard grok-imagine-image.
ByteDance Seedream 5.0 Lite
ByteDance's lightweight Seedream 5.0 image editing model, delivering fast, high-fidelity transformations with exceptional face preservation and multi-reference support.
Start building with Qwen Image
No API keys required. Create AI-powered workflows with Qwen Image in minutes — free.