head to head · open source

headroom vs Mem0

headroom has 72,745 GitHub stars, 5,589 forks, 643 open issues and last shipped yesterday. Mem0 has 65,505 stars, 7,683 forks, 742 open issues and last shipped yesterday. headroom leads on adoption by 11% (72,745 vs 65,505 stars). headroom is written in Python under Apache-2.0; Mem0 is written in Python under Apache-2.0. headroom has attracted 8% as many forks as stars, Mem0 12%. 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 Mem0 ★ 66K category AI & Machine Learning

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Side by side

headroom Mem0
GitHub stars ★ 73K ★ 66K
License Apache-2.0 Apache-2.0
Written in Python Python
Last push 2026-09-17 2026-09-17
Forks ⑂ 5.6K ⑂ 7.7K
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 Mem0 if

  • You want the Mem0 feature set and don't need the biggest community
  • You prefer the Apache-2.0 license terms
  • Your stack matches Python
  • You evaluated both and Mem0 fits your workflow better

full Mem0 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 Mem0

Mem0 is an open source memory layer for AI agents and applications, designed to store, retrieve, and manage persistent context across interactions. It lives in the Python based AI development ecosystem and provides infrastructure that enables agents and apps to remember user preferences, conversation history, and state over time—moving beyond ephemeral chat sessions toward truly adaptive systems.

read the full Mem0 overview →

More in AI & Machine Learning

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

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dify vs langchain dify vs ponytail langchain vs ponytail dify vs graphify langchain vs graphify ponytail vs graphify dify vs claude-mem dify vs ragflow openclaw vs hermes-agent openclaw vs open-webui openclaw vs lobechat openclaw vs anythingllm openclaw vs cherry-studio openclaw vs nanobot openclaw vs jan openclaw vs librechat ollama vs llama-cpp ollama vs vllm ollama vs gpt4all ollama vs llama-index ollama vs localai llama-cpp vs vllm ollama vs pageindex ollama vs langfuse

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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 daily_stock_analysis headroom vs LiteLLM headroom vs Multica

Frequently asked questions

Is headroom or Mem0 more popular?

headroom has 72,745 GitHub stars and Mem0 has 65,505. headroom has the larger community by that measure.

Are headroom and Mem0 free?

Both are open source. headroom is licensed under Apache-2.0 and Mem0 under Apache-2.0. Neither carries a licence fee.

What is the difference between headroom and Mem0?

headroom is written in Python and Mem0 in Python. 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 Mem0?

Choose headroom if you want the larger community (72,745 stars) or its Apache-2.0 licence terms. Choose Mem0 if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.