agentmemory vs mem0
mem0 is much bigger: 64.7k stars against 28.0k. Over the days we have tracked them agentmemory moved +25.3% and mem0 +6.1%, so agentmemory is growing faster right now.
agentmemory leads on context depth and model freedom. mem0 does not take any axis by a clear margin.
Stars and commit dates come from our own daily tracking. The six axes are read off each project's documentation by our review pipeline, so they describe what a project says about itself, not what we measured in its code.
Where they stand today
Provides a local, multi-agent persistent memory server with hybrid retrieval and confidence scoring that shares memories across any MCP/HTTP agent.
- Stars
- 28.0k
- Tracked growth
- +25.3%
- Maturity
- ●●●●●
- Last commit
- 5d ago
- Language
- TypeScript
- License
- Apache-2.0
- Cost to run
- Free to run locally; optional cloud API keys for agent LLMs.
Provides a production-ready, self-hostable memory layer with a token-efficient memory algorithm, entity linking, and agent skills for easy integration into AI assistants.
- Stars
- 64.7k
- Tracked growth
- +6.1%
- Maturity
- ●●●●●
- Last commit
- 18h ago
- Language
- Python
- License
- Apache-2.0
- Cost to run
- Your LLM/API key costs; self-host or paid cloud available
Six axes, head to head
Each axis runs 0 to 5. The label under a score is what that project's own docs claim, not a category average.
| Axis | agentmemory | mem0 |
|---|---|---|
Context depth How much of your codebase it sees before it answers: the open diff, the diff plus related files, or the whole repository. | ●●●●● Diff + related files | ●●●●● User/session only |
Noise control How it keeps output volume down — severity thresholds, deduplication, incremental runs over new commits only. | ●●●●● Confidence scoring | ●●●●● Multi-signal retrieval |
Customization How far it bends to your team: custom rules, prompts, style guides, per-path config. | ●●●●● Config file options | ●●●●● Plugins & config |
Privacy Whether your code stays on your own infrastructure: fully local, self-hostable, or cloud API only. | ●●●●● Fully local | ●●●●● Self-hostable |
Model freedom Whether you can point it at any provider, or it is wired to one. | ●●●●● Provider-agnostic | ●●●●● Multiple LLMs |
Setup ease What it takes to get a first useful run out of it. | ●●●●● One-command setup | ●●●●● One-command start |
Which one to pick
Pick agentmemory if…
Easy setup — one-command local memory server with a demo and adapters for many coding agents, preserving session memory across restarts.
- Context depth: Diff + related files (3/5 against 1/5)
- Model freedom: Provider-agnostic (5/5 against 3/5)
Pick mem0 if…
Self-hostable — one-command bootstrap and SDKs let teams add a scalable, token-efficient memory layer while keeping data under their control.
What people want from each one
rohitg00/agentmemory
mem0ai/mem0
Hacker News: Show HN: Mem0 – open-source Memory Layer for AI apps drew 201 points and 61 comments.
Questions people ask
Is agentmemory better than mem0?
agentmemory leads on context depth and model freedom. mem0 does not take any axis by a clear margin. agentmemory is worth picking when easy setup — one-command local memory server with a demo and adapters for many coding agents, preserving session memory across restarts.
Which of agentmemory and mem0 keeps my code private?
agentmemory: Fully local (5/5). mem0: Self-hostable (4/5).
What does each one cost to run?
agentmemory: Free to run locally; optional cloud API keys for agent LLMs.. mem0: Your LLM/API key costs; self-host or paid cloud available.
Full profiles: rohitg00/agentmemory and mem0ai/mem0. Everything else in Memory & context.