faiss
The quiet backbone of the vector-database era
Latest: v1.15.0 (Aug 2026)
The library for efficient similarity search and clustering of dense vectors, with CPU and GPU indexes that scale to billions of vectors. Open-sourced by FAIR in 2017, faiss became foundational plumbing for the vector-database and RAG era — its algorithms are embedded in OpenSearch, Milvus and many commercial vector stores.
Why it matters
The reference library for nearest-neighbor search over billions of dense vectors on CPU or GPU. Open-sourced in 2017, it became the plumbing of the vector-database and RAG era: its indexes are embedded in OpenSearch, Milvus and many commercial vector stores, and a faiss index is still the default first step for embedding search.
Facts
- 41k GitHub stars (Sept 2026) — the most-starred facebookresearch repo after Segment Anything.
- The 2017 launch demonstrated billion-scale GPU k-NN search; the 2024 paper 'The Faiss library' (arXiv 2401.08281) documents a decade of tricks.
- Practically every RAG stack touches faiss or an index it inspired.
Try it yourself
pip install faiss-cpu ↗ Getting started (wiki) ↗ Code on GitHub ↗
Sources
arXiv ↗GitHub · faiss · faiss ↗GitHub · faiss · wiki ↗