A main-push SDK Java run failed its 'ubuntu-latest / Java 21' leg in the Checkout step before any test ran (run 37423974280). The leg runs on the shared self-hosted ECS pool, whose reused workspace accumulates residue from earlier jobs: ci.yml's incident history records review/autofix leftovers (.qwen, .qwen.root-orig, review worktrees and branches) failing actions/checkout's clean, and a runner-user-owned tree failing every later git call with 'detected dubious ownership' (#12648). sdk-java.yml's pool-routed jobs carried only the bare ownership restore, without the two countermeasures ci.yml grew for exactly these failures. Port both, byte-identical to the pinned ci.yml copies, to the three pool-routed jobs (test, flyway-migrations, daemon-e2e): the safe.directory trust joins the restore step, and the stale-.qwen sweep (with its quarantine ladder and review worktree/branch cleanup) runs between restore and checkout, gated to self-hosted so the hosted macOS/Windows legs stay untouched. The sdk-java workflow suite pins the restore -> sweep -> checkout order in all three jobs and pins both step bodies byte-identical to ci.yml's, so the copies cannot drift; mutation-probed by stashing the workflow change (all 9 new pins red) and restoring it (green). The size baseline records the copied recipe's growth in the same commit, per the ratchet. Co-authored-by: 易良 <1204183885@qq.com> |
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| .github | ||
| .husky | ||
| .qwen | ||
| .vscode | ||
| docs | ||
| docs-site | ||
| eslint-rules | ||
| integration-tests | ||
| integrations | ||
| packages | ||
| patches | ||
| scripts | ||
| .dockerignore | ||
| .editorconfig | ||
| .gitattributes | ||
| .gitignore | ||
| .npmrc | ||
| .nvmrc | ||
| .pnpmfile.mjs | ||
| .prettierignore | ||
| .prettierrc.json | ||
| .yamllint.yml | ||
| AGENTS.md | ||
| CHANGELOG.md | ||
| CLAUDE.md | ||
| CONTRIBUTING.md | ||
| Dockerfile | ||
| esbuild.config.js | ||
| eslint.config.js | ||
| eslint.legacy-core-barrel-imports.mjs | ||
| eslint.legacy-filenames.mjs | ||
| LICENSE | ||
| Makefile | ||
| package.json | ||
| pnpm-lock.yaml | ||
| pnpm-workspace.yaml | ||
| README.md | ||
| SECURITY.md | ||
| tsconfig.json | ||
| vitest.config.ts | ||
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 to configure your provider and API key. Then try:
Explain this repository and show me where to start.
See the Authentication Guide and Settings Reference for detailed setup.
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.
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())
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
Evaluation Configuration
| Configuration | Value |
|---|---|
| Dataset | princeton-nlp/SWE-bench_Verified, 500 cases |
| Runs | 3 trials per version, 1,500 jobs per version; 7 Qwen Code versions |
| Model | Qwen 3.7 Max |
| Sampling | temperature=1, top_p=0.95 |
| Thinking / Reasoning | interleaved_thinking=true, thinking_type=adaptive, reasoning_effort=high |
| Context / Output Limits | context_1m=true, model_context_length=1,000,000, max_tokens=64,000, model_max_tokens=65,535 |
| Harness Limits | max_iterations=500, runtime_timeout_sec=7,200, agent_timeout_multiplier=3.0 |
Scores by Qwen Code Version
| Version | Avg Score | Pass Rate | pass@3 | pass^3 |
|---|---|---|---|---|
| 0.0.14 | 77.80% | 84.6% | 84.6% | 69.2% |
| 0.1.0 | 76.73% | 84.6% | 84.6% | 68.0% |
| 0.5.0 | 76.60% | 83.0% | 83.0% | 68.4% |
| 0.10.0 | 76.47% | 84.4% | 84.4% | 67.4% |
| 0.15.0 | 77.67% | 84.6% | 84.6% | 68.6% |
| 0.19.0 | 76.40% | 85.0% | 85.0% | 65.8% |
| 0.22.0 | 77.33% | 84.4% | 84.4% | 68.0% |
Avg Score Trend
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 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.

