1-bit quantized embeddings cut vector index storage up to 60x with <1% quality loss
burkov · x · 2026-09-07
Andriy Burkov highlights a paper showing that compressing vector embeddings with 1-bit quantization and dimension reduction before clustering cuts index storage by up to 60x and speeds up index construction, while staying within 1% of full-precision search quality — a cheap engineering win for large-scale vector retrieval.
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