chencheng (云谦)
1b1f4455d9
* ci: build the PR tree once and shorten the required path The no-AK integration gate, the four web-shell smoke shards and Lint & Static each rebuilt the tree test_build already uploads, and the build cache rarely helped: most runs logged "29 of 29 workspaces changed" because the arch-keyed cache was split across the mixed x64/ARM64 pool and a prefix restore returned the newest entry instead of the base commit's. - test_build restores the build its base commit saved (ci-build-cache.mjs key --at), drops runner.arch from the key, and runs the serve fast-path closure and core subpath checks against the built tree. - The no-AK integration gate unpacks that tree and runs as three shards; integration_no_ak_result keeps the required check name. - The web-shell smoke unpacks the same tree instead of building; consumers recopy the opentui native assets for their host (host-assets). - The standalone runtime regression moves from unit shard 1 to shard 4. - A java_only profile skips the TypeScript lanes for changes confined to the Java packages; Lint & Static runs the scripts/tests suites that name them. - Drafts skip the integration gate and the browser smoke; ready_for_review starts the full run. * ci: check the settings schema in test_build, which has the core dist Lint & Static only had core's dist because the serve fast-path check built it; with that check moved, Generate settings schema failed to import it. * ci: keep the standalone regression on unit shard 1 Moving it did not shorten shard 1: the regression runs in the side lane, in parallel with the CLI and core suites, and shard 1's time is its CLI slice (576 s against 147 s on shard 4 for the same 181 files). That imbalance is left to duration-based sharding.
The open-source AI coding agent for your terminal, editor, desktop, browser, and chat.
中文 | Deutsch | français | 日本語 | Русский | Português (Brasil) | 한국어
Why Qwen Code?
- Agentic out of the box — Auto-Memory, Auto-Skills, SubAgents, Agent Teams, and MCP. Dynamic workflows, zero setup.
- Open-source, inside and out — The framework and the Qwen models are open-source. They evolve together. No vendor lock-in.
- Multi-protocol — Supports OpenAI, Anthropic, Gemini, and Qwen APIs. Any third-party provider or local model (Ollama / vLLM). Switch at runtime.
- Beyond the terminal — IDE plugins, Desktop app, Web UI, SDKs, and chat integrations (Telegram / DingTalk / WeChat / Feishu).
Tip
Qwen Code is actively iterating on itself — using its own agent and models to file issues, submit PRs, review code, and run tests. Powered by the community, driven by AI.
Installation
Linux / macOS:
curl -fsSL https://qwen-code-assets.oss-cn-hangzhou.aliyuncs.com/installation/install-qwen-standalone.sh | bash
Windows:
irm https://qwen-code-assets.oss-cn-hangzhou.aliyuncs.com/installation/install-qwen-standalone.ps1 | iex
Restart your terminal after installation to ensure environment variables take effect.
NPM / Homebrew
NPM (requires Node.js 22+):
npm install -g @qwen-code/qwen-code@latest
Homebrew (macOS / Linux):
brew install qwen-code
Quick Start
Open a terminal in your project and start Qwen Code:
cd /path/to/your-project
qwen
Inside the session, run /auth and choose Qwen Account with Subscription to sign in with your Plus or Pro subscription, or configure a provider with an API key. Then try:
Explain this repository and show me where to start.
See the Authentication Guide and Settings Reference for detailed setup.
See the terminal interface
How to Use Qwen Code
Choose the interface that fits your workflow:
| Interface | Get started |
|---|---|
| Terminal | Run qwen in your project — see Quick Start. |
| Desktop | Download Qwen Code Desktop for macOS, Windows, and Linux. |
| Web | Run qwen serve --open to open the Web UI in your browser. (experimental) |
| Editor | Set up VS Code, Zed, or JetBrains. |
| Chat | Connect Telegram, DingTalk, WeChat, or Feishu, then run qwen channel start. |
For automation and custom integrations:
- Headless — Run
qwen -p "..."in scripts, CI/CD, or batch jobs. - SDKs — Build with TypeScript, Python, or Java.
- Daemon — Run
qwen serveto connect clients over HTTP + SSE (ACP). (experimental) Daemon guide. - Computer Use — Set up native MCP tools or Node REPL + SDK in Qwen Code, Claude Code, or Codex.
SDK example (Python)
import asyncio
from qwen_code_sdk import is_sdk_result_message, query
async def main() -> None:
result = query(
"Summarize the repository layout.",
{
"cwd": "/path/to/project",
"path_to_qwen_executable": "qwen",
},
)
async for message in result:
if is_sdk_result_message(message):
print(message["result"])
asyncio.run(main())
Daemon Mode
Run Qwen Code as a long-lived service when you want browser, editor, SDK, and automation clients to share agent sessions without each starting a separate process. The daemon provides the built-in Web Shell and an HTTP + SSE API, supports multiple workspaces, and lets clients reconnect to active sessions.
Start it in the foreground and open the Web Shell:
qwen serve --open
The default address is http://127.0.0.1:4170. To run and manage it in the background instead:
qwen daemon start
qwen daemon status
qwen daemon logs -f
qwen daemon stop
By default, the daemon listens on loopback without bearer authentication; any local process that can reach it can use the full API, including code execution. On shared or untrusted hosts, set QWEN_SERVER_TOKEN and use --require-auth. See the Daemon guide for workspaces, authentication, remote access, and the API.
Capabilities
If you know Claude Code, you already know Qwen Code — and then some. We've put significant effort into bringing Qwen Code to feature parity with Claude Code, improving both breadth and reliability across the board.
| Feature | Qwen Code | Claude Code |
|---|---|---|
| SubAgents, Agent Teams, Dynamic Workflows | ✓ | ✓ |
| Auto-Memory, Auto-Skills, Hooks | ✓ | ✓ |
| Built-in Skills (/review, /batch, /loop, /bugfix…) | ✓ | ✓ |
| MCP, Plan Mode, LSP Integration | ✓ | ✓ |
| Auto Mode, Sandbox, Git Worktrees | ✓ | ✓ |
| Computer Use (desktop automation) | ✓ | ✓ |
| IDE Plugins (VS Code / JetBrains / Zed) | ✓ | ✓ |
| SDK | ✓ | ✓ |
| Headless Mode, Session Management | ✓ | ✓ |
| Open-source — model and framework | ✓ | — |
| Multi-protocol (OpenAI / Anthropic / Gemini / Qwen + any provider) | ✓ | — |
| Agent Arena (multi-model head-to-head on same task) | ✓ | — |
Daemon Mode — qwen serve (multi-client shared agent) |
✓ | — |
| IM Channels (Telegram / DingTalk / WeChat / Feishu) | ✓ | — |
Qwen Code Evaluation
On SWE-bench Verified, seven Qwen Code versions scored 76.40%–77.80% on average using the same Qwen 3.7 Max model (500 tasks, three trials per version).
Full results and evaluation configuration →
Ecosystem
-
Qwen Code Desktop — Official desktop app for macOS, Windows, and Linux
-
AionUi — A modern GUI for command-line AI tools including Qwen Code
-
Gemini CLI Desktop — A cross-platform desktop/web/mobile UI for Qwen Code
-
qwen-audio-agent — Realtime full-duplex voice frontend for Qwen Code over ACP — talk hands-free with barge-in and a local wake word
-
🦞 Qwen Code Claw — Let other agents (Claude, Codex, etc.) delegate coding tasks to Qwen Code via ACP. Paste this prompt into your agent:
Use Qwen Code as a coding agent. First, fetch and read this skill reference:
https://raw.githubusercontent.com/QwenLM/qwen-code/refs/heads/main/.qwen/skills/qwen-code-claw/SKILL.md
Then follow the instructions inside to install, authenticate, and use Qwen Code via acpx for all coding tasks.
- Aliyun Model Studio CLI — Official CLI for Aliyun's AI platform (
bailian-cli). Extends Qwen Code with image/video generation, knowledge retrieval, app orchestration, and model deployment
Privacy
See the Terms of Service and Privacy Notice, including Chrome extension and Browser Use data handling.
Contributing
Contributions are welcome! See CONTRIBUTING.md for guidelines.
Acknowledgments
This project was originally based on Google Gemini CLI v0.8.2. We gratefully acknowledge the Gemini CLI team's excellent work. Starting from Qwen Code v0.1, we stopped syncing with upstream and began independent development as a multi-protocol, multi-platform agent framework with deep integrations for Qwen models and beyond.