fix: add –fast hint to /model description for discoverability (#3086)
Add “(–fast for suggestion model)” to the /model command description so users can discover the feature from the command list, since –fast completion no longer appears on empty input.
Co-authored-by: Claude Opus 4.6 (1M context) noreply@anthropic.com
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An open-source AI agent that lives in your terminal.
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🎉 News
2026-04-02: Qwen3.6-Plus is now live! Sign in via Qwen OAuth to use it directly, or get an API key from Alibaba Cloud ModelStudio to access it through the OpenAI-compatible API.
2026-02-16: Qwen3.5-Plus is now live!
Why Qwen Code?
Qwen Code is an open-source AI agent for the terminal, optimized for Qwen series models. It helps you understand large codebases, automate tedious work, and ship faster.
Installation
Quick Install (Recommended)
Linux / macOS
Windows (Run as Administrator CMD)
Manual Installation
Prerequisites
Make sure you have Node.js 20 or later installed. Download it from nodejs.org.
NPM
Homebrew (macOS, Linux)
Quick Start
On first use, you’ll be prompted to sign in. You can run
/authanytime to switch authentication methods.Example prompts:
Click to watch a demo video
🦞 Use Qwen Code for Coding Tasks in Claw
Copy the prompt below and paste it into your agent:
Authentication
Qwen Code supports two authentication methods:
qwen.aiaccount in a browser.Qwen OAuth (recommended)
Start
qwen, then run:Choose Qwen OAuth and complete the browser flow. Your credentials are cached locally so you usually won’t need to log in again.
API-KEY (flexible)
Use this if you want more flexibility over which provider and model to use. Supports multiple protocols:
The recommended way to configure models and providers is by editing
~/.qwen/settings.json(create it if it doesn’t exist). This file lets you define all available models, API keys, and default settings in one place.Quick Setup in 3 Steps
Step 1: Create or edit
~/.qwen/settings.jsonHere is a complete example:
Step 2: Understand each field
modelProvidersopenai,anthropic,geminirepresent the API protocol.modelProviders[].idqwen3.6-plus,gpt-4o).modelProviders[].envKeymodelProviders[].baseUrlenv.envfiles orexportfor sensitive keys).security.auth.selectedTypeopenai,anthropic,gemini,vertex-ai).model.nameStep 3: Start Qwen Code — your configuration takes effect automatically:
Use the
/modelcommand at any time to switch between all configured models.More Examples
Coding Plan (Alibaba Cloud ModelStudio) — fixed monthly fee, higher quotas
Multiple providers (OpenAI + Anthropic + Gemini)
Enable thinking mode (for supported models like qwen3.5-plus)
Usage
As an open-source terminal agent, you can use Qwen Code in four primary ways:
Interactive mode
Run
qwenin your project folder to launch the interactive terminal UI. Use@to reference local files (for example@src/main.ts).Headless mode
Use
-pto run Qwen Code without the interactive UI—ideal for scripts, automation, and CI/CD. Learn more: Headless mode.IDE integration
Use Qwen Code inside your editor (VS Code, Zed, and JetBrains IDEs):
TypeScript SDK
Build on top of Qwen Code with the TypeScript SDK:
Commands & Shortcuts
Session Commands
/help- Display available commands/clear- Clear conversation history/compress- Compress history to save tokens/stats- Show current session information/bug- Submit a bug report/exitor/quit- Exit Qwen CodeKeyboard Shortcuts
Ctrl+C- Cancel current operationCtrl+D- Exit (on empty line)Up/Down- Navigate command historyConfiguration
Qwen Code can be configured via
settings.json, environment variables, and CLI flags.~/.qwen/settings.jsonmodelProvidersandenv..qwen/settings.jsonThe most commonly used top-level fields in
settings.json:modelProvidersopenai,anthropic,gemini,vertex-ai).envexportand.envfiles.security.auth.selectedTypeopenai).model.nameBenchmark Results
Terminal-Bench Performance
Ecosystem
Looking for a graphical interface?
Troubleshooting
If you encounter issues, check the troubleshooting guide.
To report a bug from within the CLI, run
/bugand include a short title and repro steps.Connect with Us
Acknowledgments
This project is based on Google Gemini CLI. We acknowledge and appreciate the excellent work of the Gemini CLI team. Our main contribution focuses on parser-level adaptations to better support Qwen-Coder models.