head to head · open source

ragflow vs llama_index

ragflow has 90,911 GitHub stars, 10,764 forks, 1,525 open issues and last shipped today. llama_index has 52,206 stars, 8,165 forks, 770 open issues and last shipped today. ragflow leads on adoption by 74% (90,911 vs 52,206 stars). ragflow is written in Go under Apache-2.0; llama_index is written in Python under MIT. ragflow has attracted 12% as many forks as stars, llama_index 16%. ragflow was the more recently maintained of the two, and both are self-hostable with no licence fee.

Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.

ragflow ★ 91K llama_index ★ 52K category AI & Machine Learning

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Side by side

ragflow llama_index
GitHub stars ★ 91K ★ 52K
License Apache-2.0 MIT
Written in Go Python
Last push 2026-09-18 2026-09-18
Forks ⑂ 11K ⑂ 8.2K
Self-hosting Yes Yes
Data ownership Your server Your server

pick ragflow if

  • You weight community size — 91K stars and counting
  • You want the Apache-2.0 license terms
  • Your stack matches Go
  • You value the larger contributor base for long-term maintenance

full ragflow profile →

pick llama_index if

  • You want the llama_index feature set and don't need the biggest community
  • You prefer the MIT license terms
  • Your stack matches Python
  • You evaluated both and llama_index fits your workflow better

full llama_index profile →

About ragflow

RAGFlow is an open source Retrieval Augmented Generation engine that fuses RAG with agent capabilities into a context layer for large language models, built for developers and teams that need to turn complex, unstructured documents into production AI systems.

read the full ragflow overview →

About llama_index

LlamaIndex is an MIT licensed, open source Python framework for building agentic applications — retrieval augmented generation systems, agents and multi agent workflows — on top of private documents and data, and it is aimed at AI engineers and teams who need to connect large language models to their own sources of context.

read the full llama_index overview →

More in AI & Machine Learning

OpenClaw ★ 390K Hermes Agent ★ 247K Ollama ★ 181K Dify ★ 156K Open WebUI ★ 152K langchain ★ 147K

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ollama vs llama-index openclaw vs ollama ollama vs llama-cpp ollama vs vllm ollama vs gpt4all ollama vs localai open-webui vs gpt4all llama-cpp vs vllm openclaw vs dify openclaw vs multica openclaw vs langgraph n8n vs dify dify vs langflow dify vs open-webui dify vs langchain dify vs ponytail openclaw vs hermes-agent openclaw vs opencode openclaw vs n8n openclaw vs open-webui openclaw vs lobechat openclaw vs anythingllm hermes-agent vs opencode hermes-agent vs n8n

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Compare either of these against the rest of the AI Development Platforms field.

ragflow vs Dify ragflow vs langchain ragflow vs ponytail ragflow vs generative-ai-for-beginners ragflow vs graphify ragflow vs claude-mem ragflow vs PaddleOCR ragflow vs Agent-Reach ragflow vs headroom ragflow vs Mem0 ragflow vs daily_stock_analysis ragflow vs LiteLLM

Frequently asked questions

Is ragflow or llama_index more popular?

ragflow has 90,911 GitHub stars and llama_index has 52,206. ragflow has the larger community by that measure.

Are ragflow and llama_index free?

Both are open source. ragflow is licensed under Apache-2.0 and llama_index under MIT. Neither carries a licence fee.

What is the difference between ragflow and llama_index?

ragflow is written in Go and llama_index in Python. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.

Which should I choose, ragflow or llama_index?

Choose ragflow if you want the larger community (90,911 stars) or its Apache-2.0 licence terms. Choose llama_index if its feature set, stack or MIT licence fits better. Both are self-hostable.