headroom vs MemOS
Side-by-side comparison of two AI agent tools
h
headroomopen-source
Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 20% fewer tokens for coding agents, 60-95% fewer tokens for JSON, same answers. Li
M
MemOSopen-source
Self-evolving memory OS for LLM & AI Agents: ultra-persistent memory, hybrid-retrieval, and cross-task skill reuse, with 35.24% token savings and DeepSeek Harne
Metrics
| headroom | MemOS | |
|---|---|---|
| Stars | 74.2k | 11.7k |
| Star velocity /mo | 6.2k | 971.6666666666666 |
| Commits (90d) | 1.2k | 264 |
| Releases (6m) | 10 | 10 |
| Overall score | 0.91550535160014 | 0.730926100634913 |
FAQ
- Which is more popular, headroom or MemOS?
- headroom has more GitHub stars (74,176 vs 11,660).
- Which is more actively developed, headroom or MemOS?
- headroom had more commits in the last 90 days (1,163 vs 264).
- 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.