📖 The AI Tool Bible

LlamaIndex vs RAGFlow

A side-by-side look at pricing, capabilities, pros, cons, and our editorial scores.

 
LlamaIndex
RAG
RAGFlow
RAG
TaglineData framework for connecting LLMs to your data.Open-source RAG engine with deep document parsing, hybrid search, and visual agent orchestration.
CategoryRAGRAG
PricingFreemium· Free open-source; LlamaCloud paidFreemium· Free tier; Starter $29/mo; Pro $129/mo; Enterprise custom
ModelBYO (Claude / GPT / open)Multi-model
Editorial score8.7 / 10—
Use cases
RAGdata ingestionindexing
document-qaenterprise-searchagent-orchestrationknowledge-basehybrid-retrieval
Pros
  • Focused on retrieval (not general agent stuff)
  • Many ingestion connectors
  • Strong production patterns
  • LlamaCloud for managed ingestion
  • Strong deep-document parsing for messy PDFs, tables, and scans
  • Hybrid vector + BM25 retrieval with citation-grounded answers
  • Fully open-source with active GitHub repo and self-host option
  • Visual agent builder plus MCP integration for tool-calling clients
  • Model-agnostic; works with most major LLM providers
Cons
  • API surface is large
  • Documentation can be hard to navigate
  • Free tier blocks API access, pushing real use to paid plans
  • Self-hosting is non-trivial and resource-hungry
  • Documentation and UI lag behind the engine's capabilities
Websitewww.llamaindex.airagflow.io
Pick LlamaIndex if
  • ✅ Focused on retrieval (not general agent stuff)
  • ✅ Many ingestion connectors
  • ✅ Strong production patterns
  • ✅ LlamaCloud for managed ingestion
Pick RAGFlow if
  • ✅ Strong deep-document parsing for messy PDFs, tables, and scans
  • ✅ Hybrid vector + BM25 retrieval with citation-grounded answers
  • ✅ Fully open-source with active GitHub repo and self-host option
  • ✅ Visual agent builder plus MCP integration for tool-calling clients
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