head to head · open source
llama_index vs LightRAG
llama_index has 52,779 GitHub stars, 8,500 forks, 770 open issues and last shipped 8 days ago. LightRAG has 40,487 stars, 5,752 forks, 222 open issues and last shipped 5 days ago. llama_index leads on adoption by 30% (52,779 vs 40,487 stars). llama_index is written in Python under MIT; LightRAG is written in Python under MIT. llama_index has attracted 16% as many forks as stars, LightRAG 14%. LightRAG was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 2 topic tags (llm, rag), so they are genuine substitutes rather than adjacent tools.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
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Side by side
| llama_index | LightRAG | |
|---|---|---|
| GitHub stars | ★ 53K | ★ 40K |
| License | MIT | MIT |
| Written in | Python | Python |
| Last push | 2026-10-26 | 2026-10-29 |
| Forks | ⑂ 8.5K | ⑂ 5.8K |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick llama_index if
- You weight community size — 53K stars and counting
- You want the MIT license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick LightRAG if
- You want the LightRAG feature set and don't need the biggest community
- You prefer the MIT license terms
- Your stack matches Python
- You evaluated both and LightRAG fits your workflow better
About llama_index
🗂️ LlamaIndex (OSS Framework) 🦙 [!NOTE] The current focus of LlamaIndex is to build the best AI powered engine for document parsing and extraction. LlamaParse is our enterprise platform for agentic OCR, parsing, extraction, indexing and more. LiteParse represents our efforts to build the best free, fast, cheap text parser in the market. ParseBench and ExtractBench represent our commitment towards open benchmarking for parsing and extraction. The company itself has undergone an evolution since when this OSS framework first launched 3 years ago in 2023. Since the early days, the framework has consisted of a…
read the full llama_index overview →
About LightRAG
🚀 LightRAG: Simple and Fast Retrieval Augmented Generation 🎉 News [2026.07]🎯[New Feature]: Add Smart Heading recognition feature for word documents. [2026.05]🎯[New Feature]: Merge RagAnything into LightRAG 🎉. Multimodal content parsing and extraction via MinerU / Docling services. [2026.05]🎯[New Feature]: Introducing four selectable text chunking strategies: Fix , Recursive , Vector , and Paragraph . [2026.05]🎯[New Feature]: Role specific LLM configuration support, 4 distinct roles: EXTRACT, QUERY, KEYWORDS, and VLM, with independent LLM settings. [2026.03]🎯[New Feature]: Integrated OpenSearch as a…
read the full LightRAG overview →
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Frequently asked questions
Is llama_index or LightRAG more popular?
llama_index has 52,779 GitHub stars and LightRAG has 40,487. llama_index has the larger community by that measure.
Are llama_index and LightRAG free?
Both are open source. llama_index is licensed under MIT and LightRAG under MIT. Neither carries a licence fee.
What is the difference between llama_index and LightRAG?
llama_index is written in Python and LightRAG 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, llama_index or LightRAG?
Choose llama_index if you want the larger community (52,779 stars) or its MIT licence terms. Choose LightRAG if its feature set, stack or MIT licence fits better. Both are self-hostable.