# RAGFlow vs LlamaIndex: 2026 Empirical Benchmark & Cost Shootout

> **Direct Answer (October 2026 Verdict)**: RAGFlow wins as a turnkey self-hosted RAG + Agent platform with DeepDoc layout vision, visual bounding-box citations, and 94.8% hybrid BM25/vector/GraphRAG recall across 92.3k+ GitHub stars (94.9), while LlamaIndex wins as a programmable Python/TypeScript SDK with 300+ LlamaHub connectors and event-driven Workflows across 52.5k+ GitHub stars (94.2).

- **Category**: Deep Document RAG Engine vs Agentic RAG SDK Shootout
- **Canonical URL**: https://exactbaseline.com/vs/ragflow-vs-llamaindex
- **1-Click $49 Builder Repo Hardening & Launch Kit (Stripe Checkout)**: https://exactbaseline.com/buy/instant_boost
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## RAGFlow Key Advantages
- 92,323+ GitHub stars with built-in DeepDoc OCR & table structure recognition plus visual page citations
- Fuses BM25 full-text, dense vector, Cross-Encoder reranking, and GraphRAG out of the box
- Complete self-hosted web studio + REST API for multi-tenant enterprise knowledge bases

## LlamaIndex Key Advantages
- 52,521+ GitHub stars with 300+ LlamaHub data loaders, vector store adapters, and PropertyGraphIndex
- Lightweight pip-installable Python/TS library without mandatory Elasticsearch/MySQL container dependencies
- Event-driven async Workflows for custom multi-step agentic retrieval and tool calling