head to head · open source
llama_index vs PageIndex
llama_index has 52,202 GitHub stars, 8,162 forks, 770 open issues and last shipped yesterday. PageIndex has 35,678 stars, 3,148 forks, 103 open issues and last shipped yesterday. llama_index leads on adoption by 46% (52,202 vs 35,678 stars). llama_index is written in Python under MIT; PageIndex is written in Python under MIT. llama_index has attracted 16% as many forks as stars, PageIndex 9%. llama_index was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 4 topic tags (agents, llm, rag, vector-database), 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 | PageIndex | |
|---|---|---|
| GitHub stars | ★ 52K | ★ 36K |
| License | MIT | MIT |
| Written in | Python | Python |
| Last push | 2026-09-17 | 2026-09-17 |
| Forks | ⑂ 8.2K | ⑂ 3.1K |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick llama_index if
- You weight community size — 52K stars and counting
- You want the MIT license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick PageIndex if
- You want the PageIndex feature set and don't need the biggest community
- You prefer the MIT license terms
- Your stack matches Python
- You evaluated both and PageIndex fits your workflow better
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 →
About PageIndex
PageIndex is a vectorless, reasoning based retrieval augmented generation engine written in Python and released under the MIT license. It lives in the AI and machine learning infrastructure ecosystem, with topics spanning RAG, information retrieval, LLM reasoning, context engineering, and agentic AI. Instead of building a vector index, PageIndex generates a hierarchical tree index for each document and then lets a large language model reason its way through that tree, in the same way a human expert turns to the right section of a long report. The project ships as a Python SDK, a hosted cloud service, and a docume…
read the full PageIndex overview →
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Frequently asked questions
Is llama_index or PageIndex more popular?
llama_index has 52,202 GitHub stars and PageIndex has 35,678. llama_index has the larger community by that measure.
Are llama_index and PageIndex free?
Both are open source. llama_index is licensed under MIT and PageIndex under MIT. Neither carries a licence fee.
What is the difference between llama_index and PageIndex?
llama_index is written in Python and PageIndex 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 PageIndex?
Choose llama_index if you want the larger community (52,202 stars) or its MIT licence terms. Choose PageIndex if its feature set, stack or MIT licence fits better. Both are self-hostable.