MemOS vs OmO
Side-by-side comparison of two AI agent tools
Short answer
- OmO is growing faster: +810 GitHub stars in the last 30 days vs +220 for MemOS.
- Pick MemOS for: memory OS for LLMs and AI agents with graph-structured, multimodal storage and retrieval. Pick OmO for: omO: Just type "mass ulw" keyword with your prompt.
From GitHub data refreshed daily.
M
MemOSopen-source
Memory OS for LLMs and AI agents with graph-structured, multimodal storage and retrieval
O
OmOopen-source
OmO: Just type "mass ulw" keyword with your prompt. Now you are the master of graph engineering.
Metrics
| MemOS | OmO | |
|---|---|---|
| Stars | 11.7k | 69.8k |
| Star velocity /mo | 220 | 810 |
| Commits (90d) | 260 | 9.7k |
| Releases (6m) | 10 | 10 |
| Downloads (30d, npm + PyPI) | 1.5K | 91.7K |
| Overall score | 0.6983179212295428 | 0.8973547831718989 |
FAQ
- Which is more popular, MemOS or OmO?
- OmO has more GitHub stars (69,768 vs 11,682).
- Which is more actively developed, MemOS or OmO?
- OmO had more commits in the last 90 days (9,692 vs 260).
- Should I use MemOS or OmO?
- 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.