Qwen Code is an open-source AI coding agent that lives in your terminal. Developed by Alibaba's Qwen team, it edits code, runs tools, and works with whichever model provider you point it at — including local models.

Overview

Unlike AI coding assistants that live inside an IDE, Qwen Code operates directly in your terminal. It is model-agnostic: the same CLI drives Qwen, OpenAI, Anthropic and Gemini endpoints, or a local model served by Ollama or vLLM.

The project moves quickly — the GitHub repository was created on 26 June 2025 and had reached v0.19.7 by July 2026. Check the releases page for the current version rather than relying on any number quoted here.

Qwen Code is open source (Apache 2.0) and written in TypeScript, requiring Node.js 22 or later when installed via npm.

Key Features

Agentic Out of the Box: Qwen's own summary lists Auto-Memory, Auto-Skills, SubAgents, Agent Teams, and MCP support, with dynamic workflows and zero setup.
Open Source, Inside and Out: Both the framework and the Qwen models are open source, so they can evolve together without vendor lock-in.
Multi-Protocol and Model-Agnostic: Supports OpenAI, Anthropic, Gemini and Qwen APIs, plus any third-party provider or local model via Ollama or vLLM. Providers can be switched at runtime.
Beyond the Terminal: IDE plugins, a desktop app, daemon mode, SDKs, and IM bots for Telegram, DingTalk, WeChat and Feishu.
Model Context Protocol (MCP): Native support for connecting external tools and data sources.
Approval Before Changes: Agent actions that touch the file system are surfaced for approval.

How It Works

Qwen Code uses advanced AI models to understand code and provide intelligent assistance. The process involves:

Code Analysis: Analyzes code context and project structure
Pattern Recognition: Identifies coding patterns and conventions
Intelligent Editing: Uses fuzzy matching to accurately identify code sections for modification
Safe Execution: Presents changes for approval before implementation

Technical Architecture:

Language: TypeScript; requires Node.js 22+ when installed from npm
Licence: Apache 2.0
Models: Any OpenAI-, Anthropic-, Gemini- or Qwen-compatible endpoint, plus local models via Ollama or vLLM
CLI Interface: Terminal-based command-line tool (qwen)
Extensibility: MCP servers, SubAgents, Agent Teams, Auto-Skills
Cross-Platform: Windows, macOS, and Linux
Open Source: Available on GitHub with active development

Use Cases

Code Development

Code Generation: Quickly generate code snippets and functions
Code Editing: Modify and refactor existing code with AI assistance
Code Understanding: Get explanations and insights about code
Problem Solving: Search for solutions and documentation

Development Workflows

Rapid Prototyping: Quickly build and iterate on applications
Bug Fixing: Identify and fix issues with AI assistance
Refactoring: Safely refactor code while maintaining functionality
Documentation: Generate and update code documentation

Learning & Exploration

Learning New Technologies: Get code examples and explanations
Exploring Codebases: Understand unfamiliar code more quickly
Documentation Lookup: Quick access to documentation and examples
Best Practices: Learn coding best practices through AI suggestions

Team Collaboration

Consistent Code Style: AI assistance helps maintain coding standards
Faster Onboarding: New team members can get up to speed more quickly
Knowledge Sharing: MCP servers let teams share the same tools and data sources with the agent
Code Review Assistance: Better understanding of code changes

Pricing & Access

Open Source

Free: The tool itself is free and Apache 2.0 licensed
GitHub: Available on GitHub with full source code
Community Support: Active community and open development
No Subscription: Core functionality available without paid plans
Model Costs: You pay whichever model provider you point it at, or nothing if you run locally authentication

Getting Started

Step 1: Install Qwen Code

Linux / macOS:

curl -fsSL https://qwen-code-assets.oss-cn-hangzhou.aliyuncs.com/installation/install-qwen-standalone.sh | bash

Windows (PowerShell):

irm https://qwen-code-assets.oss-cn-hangzhou.aliyuncs.com/installation/install-qwen-standalone.ps1 | iex

Or via npm (needs Node.js 22+), or Homebrew:

npm install -g @qwen-code/qwen-code@latest
# or
brew install qwen-code

Restart your terminal afterwards so the environment variables take effect.

Step 2: Launch and Authenticate

qwen          # Launch the interactive terminal UI
# Inside the session:
/auth         # Configure your provider and API key

Step 3: Start Using

Navigate to your project directory
Run qwen and describe what you want changed
Review and approve file-system changes when prompted

Best Practices

Clear Instructions: Provide specific, clear instructions for better results
Review Changes: Always review AI-generated code before accepting
Use MCP: Connect documentation and internal data sources as MCP servers
Editor Integration: Use the IDE plugins or desktop app when you want a GUI alongside the CLI
Iterative Development: Use Qwen Code for step-by-step problem solving
Safety First: Review all file modifications before approval

Technical Details

System Requirements

Operating System: macOS, Windows, or Linux
Node.js: 22 or later (for the npm install path)
Terminal: Command-line interface access
Internet: Required unless you point Qwen Code at a local model

Supported Features

Code Editing: AI-powered code modification and refactoring
Editor Integration: IDE plugins and a desktop app
Multi-Model: Works with OpenAI, Anthropic, Gemini and Qwen endpoints, plus local models
Cross-Platform: Windows, macOS, and Linux support

Integration Capabilities

Terminal: Native CLI experience (qwen)
MCP: Connect external tools and data sources
IM Bots: Telegram, DingTalk, WeChat and Feishu
SDKs and Daemon Mode: For embedding Qwen Code into other systems

Limitations

Internet Dependency: Requires an internet connection unless you run a local model
Learning Curve: Takes time to learn effective usage
Fast-Moving: Releases land frequently; behaviour can change between versions
Accuracy: AI suggestions may not always be correct or optimal
Context Limits: May not always understand complex project architectures
Platform Differences: Varying behavior across different operating systems

Alternatives

Claude Code - AI-powered terminal tool from Anthropic
Cursor - AI-powered code editor with terminal integration
GitHub Copilot - AI coding assistant with IDE integration
Tabnine - AI code completion with local processing options

Community & Support

GitHub: Qwen Code Repository for source code, issues, and contributions
Releases: GitHub Releases for latest versions and changelog
Documentation: GitHub repository documentation and README
Community: Open-source community for discussions and support
Twitter/X: @Alibaba_Qwen for updates and announcements

Versions

Qwen Code releases frequently, including nightly builds. Rather than reproducing a version number that will go stale, see the GitHub releases page for the current version and changelog.

Qwen Code