Open-Source AI · LLM / RAG framework

LlamaIndex vs RAGFlow

LlamaIndex vs RAGFlow compared for 2026 — features, license, ease of use, performance and which one to choose. The data framework for RAG vs Deep-document-understanding RAG.

Updated regularly · curated by OpenSourceAI.tech

Choose LlamaIndex for developers building data-heavy RAG apps. Choose RAGFlow for RAG over messy, complex documents.

LlamaIndex vs RAGFlow at a glance

Spec	LlamaIndex	RAGFlow
Category	LLM / RAG framework	LLM / RAG framework
Type	Data / RAG framework	RAG engine
License	MIT	Apache-2.0
Runs locally	Cloud-optional	Self-hosted
Primary language	Python	Python
Ease of use	Intermediate	Intermediate
Best for	developers building data-heavy RAG apps	RAG over messy, complex documents
GitHub stars	51.2k	86.4k

How LlamaIndex and RAGFlow score

🤝 Too close to call — LlamaIndex and RAGFlow land within a hair (4.3 vs 4.5 / 5). Pick on fit, not on score.

Criterion	LlamaIndex	RAGFlow
Popularity	4.5	4.5
Maintenance	5.0	5.0
Ease of use	3.5	3.5
Privacy	3.5	4.5
License freedom	5.0	5.0

Scores are computed automatically from public signals — GitHub stars (popularity), recent commit activity (maintenance), license type (freedom), local-first design (privacy) and onboarding complexity (ease of use). Indicative, not a verdict.

What each one is

LlamaIndex

Data / RAG framework · MIT

LlamaIndex is a data framework focused on connecting LLMs to your data, with best-in-class ingestion, indexing and retrieval for RAG applications.

Best-in-class ingestion and indexing for RAG
Many data connectors and retrievers
Focused, RAG-first design

See the LlamaIndex page →

RAGFlow

RAG engine · Apache-2.0

RAGFlow is an open-source RAG engine built on deep document understanding, extracting clean structure from complex files to give LLMs grounded, cited answers.

Strong document layout understanding
Grounded answers with citations
Self-hostable web UI

See the RAGFlow page →

Key differences

LlamaIndex is data / RAG framework, while RAGFlow is rAG engine. Their licenses differ (MIT vs Apache-2.0), which matters if you ship a commercial product. They also differ in how they run (Cloud-optional vs Self-hosted). In short, LlamaIndex fits developers building data-heavy RAG apps, and RAGFlow fits RAG over messy, complex documents.

Which should you choose?

Choose LlamaIndex for developers building data-heavy RAG apps. Choose RAGFlow for RAG over messy, complex documents.

There is rarely one winner — many setups use both. The right pick depends on your hardware, your team's skills, and whether you value simplicity or control.

Frequently asked questions

Is LlamaIndex or RAGFlow easier to use?

Both sit at a similar level (Intermediate). Your choice should come down to fit rather than difficulty.

Are LlamaIndex and RAGFlow free?

LlamaIndex is free and open source (MIT), and RAGFlow is free and open source (Apache-2.0). Neither charges for the core software.

Can I run LlamaIndex and RAGFlow locally?

LlamaIndex: cloud-optional · RAGFlow: self-hosted. Both can be used without sending your data to a third-party cloud where their setup allows.

LlamaIndex vs RAGFlow — which should I pick in 2026?

Choose LlamaIndex for developers building data-heavy RAG apps. Choose RAGFlow for RAG over messy, complex documents.

People also compare

LangChain vs LlamaIndex LangChain vs RAGFlow LlamaIndex vs Haystack LlamaIndex vs DSPy LlamaIndex vs txtai LlamaIndex vs Semantic Kernel

Explore more open-source AI

Browse thousands of open-source AI tools, models and projects — all curated in one place, updated daily.

Explore the directory →