Qwen: Qwen Image
qwen/qwen-image
Access Qwen Image AI image generation using Puter.js API.
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Model Card
Qwen Image is a 20B-parameter image generation foundation model from Alibaba's Qwen series, built for text-to-image generation, image editing, and image understanding tasks.
Its standout capability is high-fidelity text rendering — it accurately places readable text in both English and Chinese within generated images, making it especially strong for posters, slides, and design-heavy visuals. Beyond text, it supports a wide range of styles from photorealism to anime, and handles advanced editing operations like style transfer, object insertion/removal, and in-image text modification.
The model also performs image understanding tasks including object detection, segmentation, depth estimation, and super-resolution. A versatile choice for developers who need generation, editing, and visual analysis in a single model. Licensed under Apache 2.0.
Cost Per Image $0.0058
per generation
Configuration N/A
resolution
Release Date Aug 1, 2025
Code Example
Use Qwen Image in your app with the Puter.js AI API — no API keys or setup required.
// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.txt2img("A serene mountain landscape at sunset", {
model: "qwen/qwen-image"
}).then(image => {
document.body.appendChild(image);
});
<html>
<body>
<script src="https://js.puter.com/v2/"></script>
<script>
puter.ai.txt2img("A serene mountain landscape at sunset", {
model: "qwen/qwen-image"
}).then(image => {
document.body.appendChild(image);
});
</script>
</body>
</html>
More AI Models From Qwen
Qwen3.8 2.4T A95B
Qwen3.8 2.4T A95B is Alibaba's open-weight release of its Qwen3.8 Max flagship, a sparse mixture-of-experts model with 2.4 trillion total parameters and 95 billion active per token, routed across 512 experts. It uses a hybrid attention design (Gated DeltaNet and Gated Attention layers) across 92 layers, with a native 262K context window and thinking mode enabled for every response. Alibaba reports 93.0 on PaperBench (ahead of GPT-5.6 Sol's 90.5), 92.6 on GPQA Diamond, 86.6 on Terminal-Bench 2.1, and 67.7 on SWE-bench Pro, positioning it for coding, research, and long-horizon agentic work. It gives developers access to Qwen-Max-class capability under open weights, useful for teams that want frontier-level coding and agentic performance without a closed API.
ChatQwen3.8 Max
Qwen3.8 Max is Alibaba's flagship large language model, released August 3, 2026 as the most capable model in the Qwen family to date. It uses a mixture-of-experts architecture with 2.4 trillion total parameters and about 95 billion active per request, and accepts text, image, and video input with a context window of up to 1 million tokens. Alibaba positions it for coding and long-horizon agentic work: in testing the model ran autonomously for over 10 days building a self-evolving software harness. Reported benchmarks include 93.0 on PaperBench, 82.8 on IFBench, 86.6 on Terminal-Bench 2.1, and 86.1 on OSWorld-Verified, ahead of Claude Opus 4.8 on several coding and agent tasks and roughly matching Claude Fable 5 and GPT-5.6 Sol, though it trails both on some evaluations. On the Arena.AI leaderboard it ranks as the top Chinese model for text tasks. Alibaba plans to open-source the weights on Hugging Face and ModelScope.
ChatQwen3.7 Flash
Qwen3.7 Flash is the low-cost, fast tier of Alibaba's Qwen3.7 family, released in July 2026. It is a vision-language model that accepts text, image, and video input across a 1 million-token context window, with reasoning enabled by default and a 262K-token thinking budget. Alibaba positions it as an upgrade over Qwen3.6 Flash in multimodal understanding and agent execution, with better object recognition and spatial intelligence. It supports function calling and structured outputs. Pricing is tiered by prompt length. Requests under 32K input tokens cost $0.03/$0.13 per million, rising to $0.20/$0.80 above 256K. Alibaba published no benchmarks at launch. An independent vision evaluation by Roboflow measured strong object identification (84.4%) but weak OCR and object detection, so it fits high-volume multimodal tasks (classification, visual agents, lightweight extraction) better than document-heavy pipelines.
Frequently Asked Questions
You can access Qwen Image by Qwen through Puter.js AI API. Include the library in your web app or Node.js project and start making calls with just a few lines of JavaScript — no backend and no configuration required.
Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add Qwen Image to your app at no cost — your users pay for their own AI usage directly, making it completely free for you as a developer.
| Price | |
|---|---|
| Per image | $0.0058 |
Qwen Image was created by Qwen and released on Aug 1, 2025.
Yes — the Qwen Image API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.
Get started with Puter.js
Add Qwen Image image generation to your app without worrying about API keys or setup.
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