MemOS vs Supermemory
Side-by-side comparison of two AI agent tools
Short answer
- Pick MemOS for: memory OS for LLMs and AI agents with graph-structured, multimodal storage and retrieval. Pick Supermemory for: memory and context engine + app that is extremely fast, scalable, and can be run fully locally.
From GitHub data refreshed daily.
M
MemOSopen-source
Memory OS for LLMs and AI agents with graph-structured, multimodal storage and retrieval
S
Supermemoryopen-source
Memory and context engine + app that is extremely fast, scalable, and can be run fully locally. The Memory API for the AI era.
Metrics
| MemOS | Supermemory | |
|---|---|---|
| Stars | 11.7k | 31.1k |
| Star velocity /mo | 220 | 280 |
| Commits (90d) | 260 | 187 |
| Releases (6m) | 10 | 10 |
| Downloads (30d, npm + PyPI) | 1.5K | — |
| Overall score | 0.6983179212295428 | 0.730923354028454 |
FAQ
- Which is more popular, MemOS or Supermemory?
- Supermemory has more GitHub stars (31,067 vs 11,682).
- Which is more actively developed, MemOS or Supermemory?
- MemOS had more commits in the last 90 days (260 vs 187).
- Should I use MemOS or Supermemory?
- 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.