MemOS vs RAGFlow

MemOS is free, with no paid plan attached. RAGFlow is free, with no paid plan attached. 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.

MemOS vs RAGFlow — straight answers

MemOS vs RAGFlow: what is the difference?

MemOS is free, with no paid plan attached and is listed for memory operating system for LLM agents with hybrid retrieval and persistent memory. RAGFlow is free, with no paid plan attached and is listed for open-source RAG engine with deep document parsing and agent workflows. Both sit in Agent Memory & RAG-as-a-Service.

Is MemOS or RAGFlow cheaper to start with?

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

Which should I choose, MemOS or RAGFlow?

Choose MemOS if you need memory operating system for LLM agents with hybrid retrieval and persistent memory; choose RAGFlow if you need open-source RAG engine with deep document parsing and agent workflows. Flocci AI Tools does not rank one above the other — it shows both feature sets side by side and lets the requirement decide.

MemOS compared with RAGFlow: pricing tier, category, listed capabilities and links.
 MemOSRAGFlow
Pricing tierFreeFree
Free to startYesYes
CategoryAI Agents & AutomationAI Agents & Automation
TypeAgent Memory & RAG-as-a-ServiceAgent Memory & RAG-as-a-Service
Listed capabilities
  • 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
  • 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
Tagsmemos memory os, agent memory, llm long term memory, open source memory for agents, memtensor memosragflow, open source rag engine, deep document understanding rag, self hosted rag
Websitememos.openmem.netragflow.io
Full pageMemOS details →RAGFlow details →
AlternativesMemOS alternatives →RAGFlow alternatives →

Basic Memory

Agent Memory & RAG-as-a-Service
free
  • 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

Cognee

Agent Memory & RAG-as-a-Service
free
  • 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

Graphiti

Agent Memory & RAG-as-a-Service
free
  • 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

LightRAG

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

Memvid

Agent Memory & RAG-as-a-Service
free
  • Packs agent memory into a single portable file with no server or database
  • Offline retrieval with no cloud dependency
  • Open source with SDKs
  • Aimed at replacing complex RAG pipelines

Letta

Agent Memory & RAG-as-a-Service
freemium
  • Free BYOK plan supporting up to 3 stateful agents
  • Stateful-agent runtime with persistent memory, desktop app, CLI and API
  • Open-source framework (formerly MemGPT) plus a managed cloud