Mem0 vs Supermemory

Mem0 is freemium — a usable free tier with paid plans above it. Supermemory is freemium — a usable free tier with paid plans above it. Both are listed under Agent Memory & RAG-as-a-Service, so this is a like-for-like comparison. Neither is ranked above the other — Flocci carries no sponsored placement.

Mem0 vs Supermemory — straight answers

Mem0 vs Supermemory: what is the difference?

Mem0 is freemium — a usable free tier with paid plans above it and is listed for free Hobby tier: unlimited end users, 10K add / 1K retrieval requests/month. Supermemory is freemium — a usable free tier with paid plans above it and is listed for free monthly usage allowance plus a Supermemory MCP server. Both sit in Agent Memory & RAG-as-a-Service.

Is Mem0 or Supermemory cheaper to start with?

Neither — Mem0 and Supermemory are both freemium, so the choice comes down to capability rather than cost. Both entries list what they uniquely do above.

Which should I choose, Mem0 or Supermemory?

Choose Mem0 if you need free Hobby tier: unlimited end users, 10K add / 1K retrieval requests/month; choose Supermemory if you need free monthly usage allowance plus a Supermemory MCP server. Flocci AI Tools does not rank one above the other — it shows both feature sets side by side and lets the requirement decide.

Mem0 compared with Supermemory: pricing tier, category, listed capabilities and links.
 Mem0Supermemory
Pricing tierFree tier + paid plansFree tier + paid plans
Free to startYesYes
CategoryAI Agents & AutomationAI Agents & Automation
TypeAgent Memory & RAG-as-a-ServiceAgent Memory & RAG-as-a-Service
Listed capabilities
  • Free Hobby tier: unlimited end users, 10K add / 1K retrieval requests/month
  • Graph memory and entity linking for agent context
  • Open-source core plus managed cloud API
  • Free monthly usage allowance plus a Supermemory MCP server
  • Native connectors for Google Drive, Notion, OneDrive as memory sources
  • Deduplication so repeated content isn't rebilled
Tagsagent memory, long term memory api, rag memory layer, persistent memory, llm memory, freememory layer, ai agent memory, personal knowledge graph, mcp memory, context api, free
Websitemem0.aisupermemory.ai
Full pageMem0 details →Supermemory details →
AlternativesMem0 alternatives →Supermemory alternatives →

Also worth comparing

All Agent Memory & RAG-as-a-Service →

MemOS

Agent Memory & RAG-as-a-Service
freeNew
  • Memory operating system for LLM agents with hybrid retrieval and persistent memory
  • Open source and self-hostable, with a cloud option
  • Built for multi-agent and personal assistants
  • Backed by MemTensor, a Shanghai team
Visit

RAGFlow

Agent Memory & RAG-as-a-Service
freeNew
  • Open-source RAG engine with deep document parsing and agent workflows
  • Grounded citations and template-based chunking
  • Self-host with Docker; bring your own LLM
Visit

Basic Memory

Agent Memory & RAG-as-a-Service
freeNew
  • MCP server that stores AI conversation memory as local Markdown notes
  • Works with Claude Desktop and other MCP clients, and is readable in Obsidian
  • Everything stays on your disk
  • Open source core is free; optional paid cloud sync
Visit

Cognee

Agent Memory & RAG-as-a-Service
freeNew
  • Open-source memory platform that turns data into a knowledge graph plus vectors for agents
  • Python API with pluggable graph, vector and relational stores
  • Self-host free; cloud option exists
Visit

Graphiti

Agent Memory & RAG-as-a-Service
freeNew
  • Framework for building real-time temporal knowledge graphs for AI agents
  • Powers Zep's memory layer; runs standalone
  • Open source, works with Neo4j and other graph DBs
Visit

LightRAG

Agent Memory & RAG-as-a-Service
freeNew
  • Simple, fast graph-based RAG from HKU Data Science lab (EMNLP 2025)
  • Combines knowledge-graph and vector retrieval
  • Works with local or hosted LLMs
Visit