mem0

<p align="center">
  <a href="https://github.com/mem0ai/mem0">
    <img src="docs/images/banner-sm.png" width="800px" alt="Mem0 - The Memory Layer for Personalized AI">
  </a>
</p>

<p align="center">
  <a href="https://luma.com/mem0-oxfm">
    <img src="docs/images/halloween-happy-hour.png" width="450px" alt="Mem0 OSS Halloween Happy Hour: The People Who Read the Source. Tuesday, Oct 27, 5:00 PM, San Francisco. Costumes encouraged.">
  </a>
  <br>
  <a href="https://luma.com/mem0-oxfm"><strong>🎃 Register here →</strong></a> · Contributors get priority
</p>



<p align="center" style="display: flex; justify-content: center; gap: 20px; align-items: center;">
  <a href="https://trendshift.io/repositories/11194" target="blank">
    <img src="https://trendshift.io/api/badge/repositories/11194" alt="mem0ai%2Fmem0 | Trendshift" width="250" height="55"/>
  </a>
</p>

<p align="center">
  <a href="https://mem0.ai">Learn more</a>
  ·
  <a href="https://mem0.dev/DiG">Join Discord</a>
  ·
  <a href="https://mem0.dev/demo">Demo</a>
</p>

<p align="center">
  <a href="https://mem0.dev/DiG">
    <img src="https://img.shields.io/badge/Discord-%235865F2.svg?&logo=discord&logoColor=white" alt="Mem0 Discord">
  </a>
  <a href="https://pepy.tech/project/mem0ai">
    <img src="https://img.shields.io/pypi/dm/mem0ai" alt="Mem0 PyPI - Downloads">
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  <a href="https://github.com/mem0ai/mem0">
    <img src="https://img.shields.io/github/commit-activity/m/mem0ai/mem0?style=flat-square" alt="GitHub commit activity">
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  <a href="https://pypi.org/project/mem0ai" target="blank">
    <img src="https://img.shields.io/pypi/v/mem0ai?color=%2334D058&label=pypi%20package" alt="Package version">
  </a>
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    <img src="https://img.shields.io/npm/v/mem0ai" alt="Npm package">
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  <a href="https://www.ycombinator.com/companies/mem0">
    <img src="https://img.shields.io/badge/Y%20Combinator-S24-orange?style=flat-square" alt="Y Combinator S24">
  </a>
</p>

<p align="center">
  <a href="https://mem0.ai/research"><strong>📄 Benchmarking Mem0's token-efficient memory algorithm →</strong></a>
</p>

## New Memory Algorithm (April 2026)

| Benchmark | Old | New  | Tokens  | Latency p50  |
| --- | --- | --- | --- | --- |
| **LoCoMo** | 71.4 | **92.5** | 7.0K  | 0.88s  |
| **LongMemEval** | 67.8 | **94.4** | 6.8K  | 1.09s  |
| **BEAM (1M)** | — | **64.1** | 6.7K  | 1.00s  |
| **BEAM (10M)** | — | **48.6** | 6.9K  | 1.05s  |

All benchmarks run on the same production-representative model stack. Single-pass retrieval (one call, no agentic loops) at a top_200 retrieval budget. Scores reflect Mem0's managed platform, which includes proprietary optimizations not available in the open-source SDK; open-source users should expect directionally similar gains but not identical numbers.

**What changed:**
- **Single-pass ADD-only extraction** -- one LLM call, no UPDATE/DELETE. Memories accumulate; nothing is overwritten.
- **Age