head to head · open source

headroom vs Suna

headroom has 72,745 GitHub stars, 5,589 forks, 643 open issues and last shipped yesterday. Suna has 20,218 stars, 3,434 forks, 74 open issues and last shipped yesterday. headroom leads on adoption by 260% (72,745 vs 20,218 stars). headroom is written in Python under Apache-2.0; Suna is written in TypeScript under a custom or non-standard licence. headroom has attracted 8% as many forks as stars, Suna 17%. headroom was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 2 topic tags (ai, llm), 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 Suna ★ 20K category AI & Machine Learning

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Side by side

headroom Suna
GitHub stars ★ 73K ★ 20K
License Apache-2.0 Custom / other
Written in Python TypeScript
Last push 2026-09-17 2026-09-17
Forks ⑂ 5.6K ⑂ 3.4K
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 Suna if

  • You want the Suna feature set and don't need the biggest community
  • You prefer the Custom / other license terms
  • Your stack matches TypeScript
  • You evaluated both and Suna fits your workflow better

full Suna 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 Suna

Suna is an open source AI Management System for autonomous AI agents that complete real world work. It lives in the AI and machine learning ecosystem, specifically AI development platforms, and presents an open source alternative to Claude Cowork and ChatGPT Work. It packages agents, shared skills, company memory, connectors, and runtime configuration into a git repository, so teams can version, diff, audit, and reuse agent logic.

read the full Suna overview →

More in AI & Machine Learning

OpenClaw ★ 390K Hermes Agent ★ 246K Ollama ★ 181K Dify ★ 156K Open WebUI ★ 152K langchain ★ 147K

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More AI Development Platforms projects

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 Suna more popular?

headroom has 72,745 GitHub stars and Suna has 20,218. headroom has the larger community by that measure.

Are headroom and Suna free?

Both are open source. headroom is licensed under Apache-2.0, and Suna has no licence declared in this registry. Both are free to self-host.

What is the difference between headroom and Suna?

headroom is written in Python and Suna 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 Suna?

Choose headroom if you want the larger community (72,745 stars) or its Apache-2.0 licence terms. Choose Suna if its feature set, stack or Custom / other licence fits better. Both are self-hostable.