OpenMemory vs MemOS

Common questions

What is the difference between OpenMemory and MemOS?

OpenMemory: Local persistent memory store for LLM applications. MemOS: Self-evolving memory OS for LLM & AI Agents. See the comparison table for live GitHub stats and shared categories.

When should I choose OpenMemory over MemOS?

Choose OpenMemory over MemOS when Requirements: Requires Python or Node.js for SDK usage; Local SQLite support by default with optional configuration for external DB like Postgres; Dependencies include TypeScript environment for setup and use; Both OpenMemory and MemOS provide local persistent memory solutions for LLM applications, with MemOS adding self-evolving capabilities and token savings; Tags unique to OpenMemory: self-hosted, vector-database, llm, ai-infrastructure; Also covers Evaluation & Observability, Model Training; - You require real long-term memory capabilities that go beyond simple embeddings in a table.

When should I choose MemOS over OpenMemory?

Choose MemOS over OpenMemory when Both OpenMemory and MemOS provide local persistent memory solutions for LLM applications, with MemOS adding self-evolving capabilities and token savings; Tags unique to MemOS: self-evolving, memory-management, agentic-ai, agent; When you require significant token savings (up to 72%) in the context of OpenClaw or Hermes agents.

When should I avoid OpenMemory?

- When a fully managed cloud service with no local setup and self-hosted capabilities is preferred - If the project specifically requires integration only with vector databases or RAG (Retrieval-Augmented Generation) systems - Projects that are not compatible with TypeScript for backend or JavaScript for application use, as OpenMemory's SDKs are built for these environments - Situations where the project cannot benefit from local-first data storage and prefers cloud-based solutions

When should I avoid MemOS?

If your application does not leverage LLMs or AI agents that are compatible with MemOS, such as Hermes or OpenClaw. In scenarios where token savings are not a priority, since MemOS's core benefit is its ability to significantly reduce token usage.

Is OpenMemory or MemOS more popular on GitHub?

MemOS has more GitHub stars (10,135 vs 4,315). Stars measure visibility, not whether either tool fits your constraints.

Are OpenMemory and MemOS open source?

Yes - both are open-source projects on GitHub (OpenMemory: Apache-2.0, MemOS: Apache-2.0).

Where can I find alternatives to OpenMemory or MemOS?

GraphCanon lists graph-backed alternatives at /tools/caviraoss-openmemory/alternatives and /tools/memtensor-memos/alternatives (/tools/caviraoss-openmemory/alternatives.md, /tools/memtensor-memos/alternatives.md), ranked by typed relationship edges rather than popularity votes.

Is there a machine-readable version of this comparison?

Yes. The markdown twin at /compare/caviraoss-openmemory-vs-memtensor-memos.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

Which is better maintained, OpenMemory or MemOS?

OpenMemory: Active. MemOS: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.

Where are the full trust reports for OpenMemory and MemOS?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: OpenMemory: /tools/caviraoss-openmemory/trust; MemOS: /tools/memtensor-memos/trust.