8 Best Supermemory Alternatives in 2026 (Open Source)
Supermemory — Memory and context engine + app that is extremely fast, scalable, and can be run fully locally. The Memory API for the AI era. Claims #1 performance on three major AI memory benchmarks with 95% recall and 99.4% context reduction.
These 8 open-source tools do the same job. They are ordered by how closely they match Supermemory, with live GitHub data so you can see which projects are actively maintained.
| Tool | GitHub stars | Stars / 30d | Last commit |
|---|---|---|---|
| Supermemory(original) | 31.0k | +2,587 | 2026-09-30 |
| Mem0 | 66.4k | +2,429 | 2026-09-25 |
| MemOS | 11.7k | +972 | 2026-09-22 |
| Memary | 2.7k | +12 | 2024-10-18 |
| Memori | 17.0k | +1,419 | 2026-09-18 |
| MemPalace | 59.4k | +4,948 | 2026-09-29 |
| Cognee | 31.2k | +2,656 | 2026-09-29 |
| Hindsight | 43.9k | +3,655 | 2026-09-30 |
| Letta | 25.0k | +515 | 2026-09-10 |
1. Mem0
Universal memory layer for AI Agents
What sets it apart: Unlike Zep (session-focused memory) or ChatGPT's built-in memory (closed, limited), Mem0 provides a standalone, open-source memory layer with proven +26% accuracy gains over OpenAI Memory, multi-level (user/session/agent) state management, and 90% token reduction via intelligent memory retrieval.
Best for: AI assistant developers who need persistent, personalized memory across conversations without building custom infrastructure; Customer support chatbots that need to recall past tickets and user preferences
2. MemOS
Self-evolving memory OS for LLM & AI Agents: ultra-persistent memory, hybrid-retrieval, and cross-task skill reuse, with 35.24% token savings and DeepSeek Harne
What sets it apart: Provides a unified memory operating system with graph-structured memory that's inspectable and editable, not just a black-box embedding store.
Best for: AI agents needing long-term memory; multi-agent collaboration systems; developers building context-aware agents
3. Memary
The Open Source Memory Layer For Autonomous Agents
What sets it apart: vs LangChain Memory / Mem0: graph-database-backed memory system emulating human memory (breadth + depth tracking) — agents automatically build and query knowledge graphs rather than flat conversation history
Best for: Building persistent, context-aware AI agents with evolving memory; User preference tracking and personalization across sessions; Multi-user agent management with separate knowledge contexts
4. Memori
Memori is agent-native memory infrastructure. A LLM-agnostic layer that turns agent execution and conversation into structured, persistent state for production
What sets it apart: Provides agent-native memory infrastructure that works with existing data systems without requiring rip-and-replace.
Best for: enterprise agent systems; production AI applications; long-conversation memory management
5. MemPalace
The best-benchmarked open-source AI memory system. And it's free.
What sets it apart: Open-source local-first memory system with verbatim storage and 96.6% R@5 performance on LongMemEval benchmarks without API calls.
Best for: developers building AI agents with persistent memory; projects requiring local-first conversation history storage; systems needing structured semantic retrieval
6. Cognee
Knowledge Engine for AI Agent Memory in 6 lines of code
What sets it apart: Unlike Mem0 (conversation memory) or Chroma (pure vector search), Cognee builds an evolving knowledge graph from documents, combining vector + graph search with cognitive science approaches, ontology grounding, and cross-agent knowledge sharing — making it AI memory infrastructure rather than just a vector database.
Best for: AI agent developers who need persistent, learning memory that combines vector search with knowledge graph relationships; Enterprise use cases requiring tenant isolation, audit trails, and cross-agent knowledge sharing
7. Hindsight
Hindsight: Agent Memory That Learns
What sets it apart: Focuses on enabling agents to learn from experience rather than just retrieving stored conversation history.
Best for: Building agents that need to learn from past interactions; Improving agent performance over long conversations; Implementing sophisticated memory systems
8. Letta
Letta is the platform for building stateful agents: AI with advanced memory that can learn and self-improve over time.
What sets it apart: Purpose-built memory architecture that enables agents to self-improve over time — vs generic agent frameworks that only have short-term chat history
Best for: Building long-running AI agents that learn from interactions; Applications requiring persistent context across sessions
FAQ
- What are the best alternatives to Supermemory?
- The closest open-source alternatives to Supermemory are Mem0, MemOS and Memary, followed by Memori, MemPalace and Cognee. They are ranked by how closely they match what Supermemory does.
- Which Supermemory alternative is the most popular?
- Mem0 has the most GitHub stars among Supermemory alternatives, with 66,380 stars.
- Which Supermemory alternative is the most actively maintained?
- By recent activity, Cognee (2,437 commits in the last 90 days) is the most actively developed alternative.