5cba899e46
Two entries in .github/workflows/qwen-autofix.md restated review-address bounds that the authoritative workflow no longer has: - af-039 said "The 300-minute job cap puts the worst case at 5 runner-hours per slot (100 across the fleet at 20)". The cap is timeout-minutes: 345 (qwen-autofix.yml:3670), so it becomes 5.75 runner-hours per slot and 115 across the fleet at the max-parallel fallback of 20 (:3679). - af-050's worst-case budget table listed "Repair 20" and "worst case 280 => job timeout 300". The Repair deterministic rejection step is bounded at 70 minutes (:5540, "the 60-minute budget below plus the same 10-minute margin"), so the row becomes 70 and the table's own six rows sum to 330, quoted against the real 345 cap. The trailing "on ubuntu-latest, whose own ceiling is 360" clause is left as-is: 345 < 360 keeps it coherent, and re-deriving the conditional runs-on expression (:3669) is out of scope. The table total is 330, leaving 15 minutes against the 345 cap. The workflow comment at :3667-3668 separately describes a 25m reserve for the four-step unarmed chain (130+60+70+60 = 320), which excludes the setup and report rows this table itemises. The two are deliberately not conflated here. Adds a test that derives every quoted figure from qwen-autofix.yml and requires the doc to agree, so neither entry can drift silently again. The existing sum check reads only the workflow and structurally cannot see a doc that restates the same numbers in prose. Witness: - red, doc unmodified: "x keeps the af-039 and af-050 budget prose in step with the job cap -> expected '# `qwen-autofix.yml` - design record...' to contain '345-minute job cap'"; Tests 9 failed | 327 passed | 14 skipped (350), rc=1 - green, both sites fixed: that test passes; Tests 8 failed | 328 passed | 14 skipped (350), rc=1. The 8 are pre-existing local-environment noise, identical to the unmodified-base baseline (Tests 8 failed | 327 passed | 14 skipped (349), rc=1). Patrol-Run: qwen-issue-patrol/jmvuqxwvapt Co-authored-by: yiliang114 <[email protected]> Co-authored-by: Qwen-Coder <[email protected]>
The open-source AI coding agent for your terminal, editor, desktop, browser, and chat.
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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.
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())
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.