Lucas Hosseini edited this page May 18, 2018 · 9 revisions


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 (versions 2 and 3). Some of the most useful algorithms are implemented on the GPU. It is developed by Facebook AI Research.

Research foundations of Faiss

Faiss is based on years of research. Most notably it implements:

This wiki

This wiki contains high-level information about Faiss and a tutorial. Navigate it using the sidebar.

Most examples are in Python for brievity, but the C++ API is exactly the same, so the translation for one to the other is trivial most of the times.

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