Binary Quantization

Also known as: BQ

Binary quantization compresses each embedding dimension down to a single bit, shrinking an index dramatically and making distance comparisons very fast with bitwise operations. The tradeoff is precision loss, so it is usually paired with a rerank step that rescores top candidates using the full-precision vectors. This two-stage approach keeps recall high while cutting memory and latency at billion-vector scale.