Comparison
Memori vs MemOS
Memori (Memory infrastructure for AI agents that captures actions and conversations into a structured, persistent state.) vs MemOS (Self-evolving memory OS for LLM & AI Agents) - live GitHub stats and typed graph relationships, not marketing.
Markdown twin · Memori alternatives · MemOS alternatives
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Tagline
- Memori
- Memory infrastructure for AI agents that captures actions and conversations into a structured, persistent state.
- MemOS
- Self-evolving memory OS for LLM & AI Agents
Stars
- Memori
- 16k
- MemOS
- 10k
Forks
- Memori
- 2.8k
- MemOS
- 920
Open issues
- Memori
- 21
- MemOS
- 158
Language
- Memori
- Python
- MemOS
- TypeScript
Adopt for
- Memori
- Memori is designed for enterprise users seeking seamless memory infrastructure that integrates with existing data architectures across multiple deployment environments.
- MemOS
- MemOS is a self-evolving memory operating system designed to enhance both Large Language Models (LLM) and AI agents. It offers ultra-persistent memory, hybrid-retrieval capabilities, and efficient cross-task skill reuse,
Persona
- Memori
- -
- MemOS
- -
Runtime
- Memori
- -
- MemOS
- -
License
- Memori
- Memori is licensed under the Apache License 2.0.
- MemOS
- Apache-2.0
Last pushed
- Memori
- Jun 15, 2026
- MemOS
- Jul 8, 2026
Categories
- Memori
- AI Agents, Model Training
- MemOS
- AI Agents, Data & Retrieval
Trust and health
Maintenance
- Memori
- Active (82%)
- MemOS
- Very active (96%)
Days since push
- Memori
- 22d
- MemOS
- 0d
Open issues (now)
- Memori
- 21
- MemOS
- 158
Security scan
- Memori
- No lockfile
- MemOS
- 2 low (2 low)
Full report
- Memori
- Trust report
- MemOS
- Trust report
Typed relationship
Memori alternative MemOSMemORI and MemOS both address the need for persistent memory infrastructure in AI agents, though MemOS emphasizes self-evolution and token efficiency.
Choose Memori if…
- Memori is primarily Python; MemOS is TypeScript.
- License: Memori is Other, MemOS is Apache-2.0.
- Pricing: Pricing details are not explicitly stated in the provided repository content..
- Requirements: The tool requires set up of an API key for Memori and your LLM.
- MemORI and MemOS both address the need for persistent memory infrastructure in AI agents, though MemOS emphasizes self-evolution and token efficiency.
- Tags unique to Memori: stateful, ai-memory, llm-agnostic, enterprise.
- Also covers Model Training.
- When you need a system to turn agent execution and conversation into structured, persistent state without disrupting your current IT environment.
When NOT to use Memori
- Avoid if you need a tool that natively extends beyond memory management to include features like autonomous agent navigation or extensive model training utilities, as Memori focuses specifically on AI
Choose MemOS if…
- MemOS is primarily TypeScript; Memori is Python.
- License: MemOS is Apache-2.0, Memori is Other.
- MemORI and MemOS both address the need for persistent memory infrastructure in AI agents, though MemOS emphasizes self-evolution and token efficiency.
- Tags unique to MemOS: self-evolving, agentic-ai, long-term-memory.
- Also covers Data & Retrieval.
- When you require significant token savings (up to 72%) in the context of OpenClaw or Hermes agents.
When NOT to use 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.
Explore
Memori trust report →MemOS trust report →AI Agents category →Model Training category →Data & Retrieval category →All comparisonsStack workflowsTrending tools
Related comparisons
Common questions
- What is the difference between Memori and MemOS?
- Memori: Memory infrastructure for AI agents that captures actions and conversations into a structured, persistent state.. MemOS: Self-evolving memory OS for LLM & AI Agents. See the comparison table for live GitHub stats and shared categories.
- When should I choose Memori over MemOS?
- Choose Memori over MemOS when Memori is primarily Python; MemOS is TypeScript; License: Memori is Other, MemOS is Apache-2.0; Pricing: Pricing details are not explicitly stated in the provided repository content.; Requirements: The tool requires set up of an API key for Memori and your LLM; MemORI and MemOS both address the need for persistent memory infrastructure in AI agents, though MemOS emphasizes self-evolution and token efficiency; Tags unique to Memori: stateful, ai-memory, llm-agnostic, enterprise; Also covers Model Training; When you need a system to turn agent execution and conversation into structured, persistent state without disrupting your current IT environment.
- When should I choose MemOS over Memori?
- Choose MemOS over Memori when MemOS is primarily TypeScript; Memori is Python; License: MemOS is Apache-2.0, Memori is Other; MemORI and MemOS both address the need for persistent memory infrastructure in AI agents, though MemOS emphasizes self-evolution and token efficiency; Tags unique to MemOS: self-evolving, agentic-ai, long-term-memory; Also covers Data & Retrieval; When you require significant token savings (up to 72%) in the context of OpenClaw or Hermes agents.
- When should I avoid Memori?
- Avoid if you need a tool that natively extends beyond memory management to include features like autonomous agent navigation or extensive model training utilities, as Memori focuses specifically on AI
- 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 Memori or MemOS more popular on GitHub?
- Memori has more GitHub stars (15,549 vs 10,135). Stars measure visibility, not whether either tool fits your constraints.
- Are Memori and MemOS open source?
- Yes - both are open-source projects on GitHub (Memori: Other, MemOS: Apache-2.0).
- Where can I find alternatives to Memori or MemOS?
- GraphCanon lists graph-backed alternatives at /tools/memorilabs-memori/alternatives and /tools/memtensor-memos/alternatives (/tools/memorilabs-memori/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/memorilabs-memori-vs-memtensor-memos.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, Memori or MemOS?
- Memori: 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 Memori and MemOS?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Memori: /tools/memorilabs-memori/trust; MemOS: /tools/memtensor-memos/trust.