head to head · open source

headroom vs qwen-code

headroom has 73,130 GitHub stars, 5,624 forks, 643 open issues and last shipped yesterday. qwen-code has 27,997 stars, 3,076 forks, 1,422 open issues and last shipped today. headroom leads on adoption by 161% (73,130 vs 27,997 stars). headroom is written in Python under Apache-2.0; qwen-code is written in TypeScript under Apache-2.0. headroom has attracted 8% as many forks as stars, qwen-code 11%. qwen-code was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 3 topic tags (ai, llm, mcp), so they are genuine substitutes rather than adjacent tools.

Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.

headroom ★ 73K qwen-code ★ 28K category AI & Machine Learning

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Side by side

headroom qwen-code
GitHub stars ★ 73K ★ 28K
License Apache-2.0 Apache-2.0
Written in Python TypeScript
Last push 2026-09-19 2026-09-20
Forks ⑂ 5.6K ⑂ 3.1K
Self-hosting Yes Yes
Data ownership Your server Your server

pick headroom if

  • You weight community size — 73K stars and counting
  • You want the Apache-2.0 license terms
  • Your stack matches Python
  • You value the larger contributor base for long-term maintenance

full headroom profile →

pick qwen-code if

  • You want the qwen-code feature set and don't need the biggest community
  • You prefer the Apache-2.0 license terms
  • Your stack matches TypeScript
  • You evaluated both and qwen-code fits your workflow better

full qwen-code profile →

About headroom

Headroom is an Apache 2.0 Python library, local proxy, agent wrapper and MCP server that compresses tool outputs, logs, files, RAG chunks and conversation history before they reach an LLM, and it is built for developers running AI coding agents or LLM applications who want to cut token usage without changing the answers they get.

read the full headroom overview →

About qwen-code

Qwen Code is an open source AI coding agent that runs in the terminal, with additional interfaces for editors, desktop, browser, and chat. It is written in TypeScript and released under the Apache 2.0 license, and it lives in the AI and machine learning ecosystem as a development platform for agentic coding. The project is maintained by QwenLM and published on npm as @qwen code/qwen code , with a documentation site hosted at qwenlm.github.io. It ships as a command line tool named qwen that opens an interactive session inside a project directory.

read the full qwen-code overview →

More in AI & Machine Learning

OpenClaw ★ 390K Hermes Agent ★ 247K Ollama ★ 181K Dify ★ 157K Open WebUI ★ 153K langchain ★ 147K

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Compare either of these against the rest of the AI Development Platforms field.

headroom vs Dify headroom vs langchain headroom vs ponytail headroom vs generative-ai-for-beginners headroom vs graphify headroom vs claude-mem headroom vs ragflow headroom vs PaddleOCR headroom vs Agent-Reach headroom vs Mem0 headroom vs daily_stock_analysis headroom vs LiteLLM

Frequently asked questions

Is headroom or qwen-code more popular?

headroom has 73,130 GitHub stars and qwen-code has 27,997. headroom has the larger community by that measure.

Are headroom and qwen-code free?

Both are open source. headroom is licensed under Apache-2.0 and qwen-code under Apache-2.0. Neither carries a licence fee.

What is the difference between headroom and qwen-code?

headroom is written in Python and qwen-code in TypeScript. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.

Which should I choose, headroom or qwen-code?

Choose headroom if you want the larger community (73,130 stars) or its Apache-2.0 licence terms. Choose qwen-code if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.