Faiss by Meta
Open-source library developed by Meta AI for efficient similarity search and clustering of dense vectors.
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detected 2026-06-24“It outperforms pgvector by 4x and significantly surpasses FAISS in disk-storage scenarios. It supports DiskANN, HNSW, and IVF+PQ indexes, maintains high performance on disk, and, best of all, is just one pip install away.”
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What does Faiss by Meta do?
Faiss (Facebook AI Similarity Search) is an open-source library developed by Meta AI. It is designed for efficient similarity search and clustering of dense vectors, capable of handling datasets from millions to billions of high-dimensional vectors. Faiss serves as a foundational component for various AI applications requiring fast nearest neighbor search.
When was Faiss by Meta founded?
Faiss by Meta was founded in 2017.
What industry does Faiss by Meta operate in?
Faiss by Meta operates in AI Foundation & Compute, Embedding Model, Vector Database, Machine Learning, Data Platform, Developer Tools.