head to head · open source
llama_index vs examples
llama_index has 52,206 GitHub stars, 8,165 forks, 770 open issues and last shipped today. examples has 3,043 stars, 1,073 forks, 64 open issues and last shipped 14 days ago. llama_index leads on adoption by 1,616% (52,206 vs 3,043 stars). llama_index is written in Python under MIT; examples is written in Jupyter Notebook under MIT. llama_index has attracted 16% as many forks as stars, examples 35%. llama_index was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 3 topic tags (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 | examples | |
|---|---|---|
| GitHub stars | ★ 52K | ★ 3.0K |
| License | MIT | MIT |
| Written in | Python | Jupyter Notebook |
| Last push | 2026-09-18 | 2026-09-04 |
| Forks | ⑂ 8.2K | ⑂ 1.1K |
| 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 examples if
- You want the examples feature set and don't need the biggest community
- You prefer the MIT license terms
- Your stack matches Jupyter Notebook
- You evaluated both and examples 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 examples
Pinecone Examples is an MIT licensed collection of Jupyter Notebooks and sample applications that lets developers get hands on with Pinecone vector databases and common AI patterns, tools, and algorithms.
read the full examples overview →
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Frequently asked questions
Is llama_index or examples more popular?
llama_index has 52,206 GitHub stars and examples has 3,043. llama_index has the larger community by that measure.
Are llama_index and examples free?
Both are open source. llama_index is licensed under MIT and examples under MIT. Neither carries a licence fee.
What is the difference between llama_index and examples?
llama_index is written in Python and examples in Jupyter Notebook. 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 examples?
Choose llama_index if you want the larger community (52,206 stars) or its MIT licence terms. Choose examples if its feature set, stack or MIT licence fits better. Both are self-hostable.