Binary Quantization For 8x Memory Reduction With Minimal Recall Loss

via “vector quantization with configurable precision loss”

Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/

Unique: Implements both product quantization and scalar quantization with quantization-aware distance metrics that account for precision loss, allowing recall to be maintained within 2-5% of full-precision search while reducing memory by 4-16x

vs others: More flexible than single-method quantization because it supports both PQ (better for high-dimensional vectors) and SQ (simpler, better for low-dimensional vectors), and quantization-aware metrics preserve recall better than naive quantization followed by standard distance computation