head to head · open source
headroom vs qwen-code
headroom has 78,773 GitHub stars, 6,155 forks, 643 open issues and last shipped yesterday. qwen-code has 28,987 stars, 3,308 forks, 1,422 open issues and last shipped yesterday. headroom leads on adoption by 172% (78,773 vs 28,987 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%. headroom 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.
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Side by side
| headroom | qwen-code | |
|---|---|---|
| GitHub stars | ★ 79K | ★ 29K |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Python | TypeScript |
| Last push | 2026-11-04 | 2026-11-04 |
| Forks | ⑂ 6.2K | ⑂ 3.3K |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick headroom if
- You weight community size — 79K 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
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
About headroom
Quickstart · Install · Proof · Agents · Docs · Discord · llms.txt AI agents / LLMs: read /llms.txt here, or fetch the live index · full docs blob . Headroom compresses everything your AI agent reads — tool outputs, logs, RAG chunks, files, and conversation history — before it reaches the LLM. Same answers, fraction of the tokens. Compression runs on your machine; no prompt or file content is sent anywhere to be compressed. 10,144 → 1,260 tokens. The same FATAL found. What it does Library — compress(messages) in Python or TypeScript, inline in any app. Proxy — headroom proxy port 8787 , zero code changes, any…
read the full headroom overview →
About qwen-code
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…
read the full qwen-code overview →
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Frequently asked questions
Is headroom or qwen-code more popular?
headroom has 78,773 GitHub stars and qwen-code has 28,987. 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 (78,773 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.