--- title: "MemOS vs memvid" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/memtensor-memos-vs-memvid-memvid" tools: ["memtensor-memos", "memvid-memvid"] --- # MemOS vs memvid Neutral, constraint-first comparison with live GitHub stats. | | [MemOS](/tools/memtensor-memos.md) | [memvid](/tools/memvid-memvid.md) | | --- | --- | --- | | Tagline | Self-evolving memory OS for LLM & AI Agents | Memory layer for AI Agents | | Stars | 10,135 | 15,736 | | Forks | 920 | 1,360 | | Open issues | 158 | 21 | | Language | TypeScript | Rust | | Adopt for | 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, | Memvid is a Rust-based single-file memory layer for AI agents that offers high accuracy, low latency, and portable long-term memory without the need for complex infrastructure. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Memvid is licensed under Apache-2.0, which allows free usage in both open-source and commercial projects with attribution. | | Categories | AI Agents, Data & Retrieval | AI Agents | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [MemOS](/tools/memtensor-memos.md) | [memvid](/tools/memvid-memvid.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Steady (60%) | | Days since push | 0d | 41d | | Open issues (now) | 158 | 21 | | Security scan | 2 low (2 low) | No lockfile | | Full report | [trust report](/tools/memtensor-memos/trust.md) | [trust report](/tools/memvid-memvid/trust.md) | **Typed relationship:** MemOS _(related)_ memvid Memvid is a memory layer for AI Agents similar to MemOS's focus on memory management, but both serve somewhat different aspects of memory infrastructure. ## Decision facts: MemOS - **Adopt for:** 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, ## Decision facts: memvid - **Requirements:** Operates independently of databases or server infrastructure. - **Adopt for:** Memvid is a Rust-based single-file memory layer for AI agents that offers high accuracy, low latency, and portable long-term memory without the need for complex infrastructure. - **License detail:** Memvid is licensed under Apache-2.0, which allows free usage in both open-source and commercial projects with attribution. ## Choose when ### Choose MemOS if… - MemOS is primarily TypeScript; memvid is Rust. - Memvid is a memory layer for AI Agents similar to MemOS's focus on memory management, but both serve somewhat different aspects of memory infrastructure. - Tags unique to MemOS: self-evolving, memory-management, agentic-ai, long-term-memory. - Also covers Data & Retrieval. - MemOS ships Docker support for self-hosted deployment. - When you require significant token savings (up to 72%) in the context of OpenClaw or Hermes agents. ### Choose memvid if… - memvid is primarily Rust; MemOS is TypeScript. - Requirements: Operates independently of databases or server infrastructure.. - Memvid is a memory layer for AI Agents similar to MemOS's focus on memory management, but both serve somewhat different aspects of memory infrastructure. - Tags unique to memvid: memory, vector-database, retrieval-augmented-generation. - - Your use case requires ultra-low latency retrieval where every millisecond counts. ## 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. ## When NOT to use memvid - - Your application demands real-time updates to memory contents across multiple agents without manual intervention. - - The use case involves large-scale data that necessitates a distributed database for handling the scale. ## Common questions ### What is the difference between MemOS and memvid? MemOS: Self-evolving memory OS for LLM & AI Agents. memvid: Memory layer for AI Agents. See the comparison table for live GitHub stats and shared categories. ### When should I choose MemOS over memvid? Choose MemOS over memvid when MemOS is primarily TypeScript; memvid is Rust; Memvid is a memory layer for AI Agents similar to MemOS's focus on memory management, but both serve somewhat different aspects of memory infrastructure; Tags unique to MemOS: self-evolving, memory-management, agentic-ai, long-term-memory; Also covers Data & Retrieval; MemOS ships Docker support for self-hosted deployment; When you require significant token savings (up to 72%) in the context of OpenClaw or Hermes agents. ### When should I choose memvid over MemOS? Choose memvid over MemOS when memvid is primarily Rust; MemOS is TypeScript; Requirements: Operates independently of databases or server infrastructure.; Memvid is a memory layer for AI Agents similar to MemOS's focus on memory management, but both serve somewhat different aspects of memory infrastructure; Tags unique to memvid: memory, vector-database, retrieval-augmented-generation; - Your use case requires ultra-low latency retrieval where every millisecond counts. ### 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. ### When should I avoid memvid? - Your application demands real-time updates to memory contents across multiple agents without manual intervention. - The use case involves large-scale data that necessitates a distributed database for handling the scale. ### Is MemOS or memvid more popular on GitHub? memvid has more GitHub stars (15,736 vs 10,135). Stars measure visibility, not whether either tool fits your constraints. ### Are MemOS and memvid open source? Yes - both are open-source projects on GitHub (MemOS: Apache-2.0, memvid: Apache-2.0). ### Where can I find alternatives to MemOS or memvid? GraphCanon lists graph-backed alternatives at /tools/memtensor-memos/alternatives and /tools/memvid-memvid/alternatives (/tools/memtensor-memos/alternatives.md, /tools/memvid-memvid/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/memtensor-memos-vs-memvid-memvid.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, MemOS or memvid? MemOS: Very active. memvid: Steady. 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 MemOS and memvid? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: MemOS: /tools/memtensor-memos/trust; memvid: /tools/memvid-memvid/trust. --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=memtensor-memos`](/api/graphcanon/graph?tool=memtensor-memos) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_