If I remember correctly, for dot product it uses BLAS libraries and for Cosine distance and L2 have very minimal SIMD support. In both cases SimSIMD should be faster for distance computations.

Multiply it by a more efficient HNSW implementation and you might be looking at a 100x performance difference on a scale of a billion vectors: https://www.unum.cloud/blog/2023-11-07-scaling-vector-search...

Thanks for the link!