AC
Public post
Avi Chawla
Sep 2026 • linkedin
Post excerpt
5 embedding compression techniques, clearly explained: (must-know for AI engineers) Ten million 1,536-dimensional embeddings will occupy: - 62 GB in float32 - 15 GB in int8 - 2 GB as packed bits This only covers the raw vector payload, and an in-memory system also needs space for the ANN index, metadata, and allocator overhead. Embedding compression works along two axes: - the number of dimensions stored - the number of bits used for each dimension The five techniques in the visual reduce different parts of the pa…
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