Compare Mem0 and Supermemory side by side. Both are tools in the Memory Layer category.
Updated March 10, 2026
Choose Mem0 if strong backing: USD 24M from top VCs including YC and Peak XV.
Choose Supermemory if production-ready.
Want to compare Mem0 and Supermemory on your own traffic?
Respan lets you trace LLM and agent calls across any model or framework, A/B test prompts on production traffic, and route requests across 250+ models through one gateway. Free tier covers 10K traces per month. Setup in 5 minutes, no credit card.
| Category | Memory Layer | Memory Layer |
| Pricing | Freemium | — |
| Best For | Developers building AI agents that need to remember user context across sessions | — |
| Website | mem0.ai | supermemory.ai |
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Mem0 is a Y Combinator-backed memory layer for AI applications founded in 2023 by Taranjeet Singh (ex-Khatabook first growth engineer) and Deshraj Yadav (ex-Tesla Autopilot AI Platform lead). Launched in January 2024, Mem0 raised USD 24 million including USD 3.9 million in seed funding and USD 20 million Series A led by Basis Set Ventures, with participation from Kindred Ventures, Y Combinator, Peak XV Partners, and GitHub Fund. The company serves over 80,000 developers and provides the exclusive memory provider for AWS new Agent SDK. Mem0 offers a free tier with 10,000 memories and 1,000 retrieval calls per month, Pro plans at USD 19-249/month with different memory limits, and custom Enterprise pricing. The platform supports both cloud-hosted and self-hosted deployment options. Graph memory capabilities are only available on Pro plans (USD 249/month) or higher. Mem0 specializes in persistent memory for LLM applications, enabling AI systems to remember context across interactions for improved personalization and continuity.
AI platform providing comprehensive solutions for enterprise applications. The platform provides essential capabilities for modern AI applications with focus on scalability and reliability.
Tools and frameworks for adding persistent, long-term memory to AI agents and LLM applications. These systems manage conversation history, user preferences, and learned context across sessions, enabling more personalized and context-aware AI interactions.
Browse all Memory Layertools →One platform for routing, observability, tracing, and evals across every LLM provider.