Mem0, Open Source Giving Memory to AI Agents [2026]

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Mem0: Adding Long-Term Memory to AI Agents

  • GitHub Stars: 46,900+
  • Language: Python (66.4%), TypeScript (20.7%)
  • License: Apache 2.0

Why This Project is Trending

Mem0 is an open-source memory layer that gives AI agents long-term memory. LLMs forget context after a conversation ends, and Mem0 solves this problem.[GitHub]

It recorded 26% higher accuracy compared to OpenAI Memory in the LOCOMO benchmark.[Mem0 Research] Response speed is 91% faster, and token consumption is reduced by 90%.

3 Key Features

  • Multi-Layered Memory: Separately stores memories by user, session, and agent.
  • Hybrid Search: Combines vector and graph search. Supports 25+ vector DBs.[Mem0 Docs]
  • LLM Auto-Tidying: LLMs handle fact extraction, conflict resolution, and memory merging.

Quick Start

# Python
pip install mem0ai

# JavaScript
npm install mem0ai

The default LLM is OpenAI gpt-4.1-nano. It can be replaced with Anthropic, Ollama, etc.

Where Can You Use It?

Apply it to customer support chatbots to remember previous inquiries. In healthcare, it can be used to track patient history. Companies like Netflix and Lemonade have already adopted it.[Mem0]

It’s a Y Combinator alum and has raised $24 million in funding.[YC]

Things to Note

  • Self-hosting requires vector DB setup. If you don’t have infrastructure experience, the cloud is easier.
  • v1.0.3 is the latest. Test thoroughly before applying to production.

Frequently Asked Questions (FAQ)

Q: What is the difference between Mem0 and general RAG?

A: General RAG retrieves documents to provide context, but Mem0 automatically extracts facts from conversations, resolves conflicts, and updates memories. It differs in that it combines vector and graph search to provide more accurate context, and it can manage user-specific memories separately.

Q: Which LLMs are compatible?

A: It is compatible with over 50 LLM providers, including OpenAI, Anthropic, and Ollama. The default is OpenAI gpt-4.1-nano, but it can be changed in the settings. It supports over 25 vector DBs, including Qdrant, Pinecone, and ChromaDB.

Q: Is it free to use?

A: The open-source version is completely free under the Apache 2.0 license. You need to build your own infrastructure. There is also a managed cloud platform, which has a separate pricing plan. If you have a small project, the open-source version is sufficient.

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References

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