head to head · open source
llama_index vs faiss
llama_index has 52,779 GitHub stars, 8,500 forks, 770 open issues and last shipped 8 days ago. faiss has 41,251 stars, 4,584 forks, 327 open issues and last shipped 2 days ago. llama_index leads on adoption by 28% (52,779 vs 41,251 stars). llama_index is written in Python under MIT; faiss is written in C++ under MIT. llama_index has attracted 16% as many forks as stars, faiss 11%. faiss 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.
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Side by side
| llama_index | faiss | |
|---|---|---|
| GitHub stars | ★ 53K | ★ 41K |
| License | MIT | MIT |
| Written in | Python | C++ |
| Last push | 2026-10-26 | 2026-11-01 |
| Forks | ⑂ 8.5K | ⑂ 4.6K |
| 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 faiss if
- You want the faiss feature set and don't need the biggest community
- You prefer the MIT license terms
- Your stack matches C++
- You evaluated both and faiss 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 faiss
Faiss Faiss is a library for efficient similarity search and clustering of dense vectors. It contains algorithms that search in sets of vectors of any size, up to ones that possibly do not fit in RAM. It also contains supporting code for evaluation and parameter tuning. Faiss is written in C++ with complete wrappers for Python/numpy. Some of the most useful algorithms are implemented on the GPU. It is developed primarily at Meta's Fundamental AI Research group. News See CHANGELOG.md for detailed information about latest features. Introduction Faiss contains several methods for similarity search. It assumes that…
read the full faiss overview →
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Frequently asked questions
Is llama_index or faiss more popular?
llama_index has 52,779 GitHub stars and faiss has 41,251. llama_index has the larger community by that measure.
Are llama_index and faiss free?
Both are open source. llama_index is licensed under MIT and faiss under MIT. Neither carries a licence fee.
What is the difference between llama_index and faiss?
llama_index is written in Python and faiss in C++. 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 faiss?
Choose llama_index if you want the larger community (52,779 stars) or its MIT licence terms. Choose faiss if its feature set, stack or MIT licence fits better. Both are self-hostable.