headroom vs MemOS
Side-by-side comparison of two AI agent tools
Short answer
- headroom is growing faster: +1,515 GitHub stars in the last 30 days vs +225 for MemOS.
- Pick headroom for: compresses tool outputs, logs, RAG chunks, files, and conversation history before they reach LLMs. Pick MemOS for: memory OS for LLMs and AI agents with graph-structured, multimodal storage and retrieval.
From GitHub data refreshed daily.
h
headroomopen-source
Compresses tool outputs, logs, RAG chunks, files, and conversation history before they reach LLMs
M
MemOSopen-source
Memory OS for LLMs and AI agents with graph-structured, multimodal storage and retrieval
Metrics
| headroom | MemOS | |
|---|---|---|
| Stars | 74.3k | 11.7k |
| Star velocity /mo | 1.5k | 225 |
| Commits (90d) | 1.2k | 261 |
| Releases (6m) | 10 | 10 |
| Overall score | 0.8896326908220638 | 0.7181250897770423 |
FAQ
- Which is more popular, headroom or MemOS?
- headroom has more GitHub stars (74,277 vs 11,675).
- Which is more actively developed, headroom or MemOS?
- headroom had more commits in the last 90 days (1,208 vs 261).
- Should I use headroom or MemOS?
- Compare their capabilities, limitations and "best for" notes above. Both are open source, so trying each on a small task is the fastest way to decide.