ModelRefs / Product Quantization (PQ) — AI Glossary
Product Quantization (PQ) — AI Glossary
A vector compression technique splitting high-dimensional vectors into sub-vectors quantized independently, reducing memory 16–64×.
Overview
PQ (Jégou et al. 2011) divides a d-dimensional vector into M sub-vectors of d/M dimensions, quantizes each to a codebook of 256 centroids (1 byte per sub-vector). An IVF-PQ index can store 1B 768-dim vectors in ~6 GB vs 3 TB for float32. Asymmetric distance computation enables accurate search despite compression.
Reference details
| Topic | rag |
|---|---|
| Last reviewed | 2026-06-24 |
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Frequently asked questions
What is Product Quantization (PQ)?
A vector compression technique splitting high-dimensional vectors into sub-vectors quantized independently, reducing memory 16–64×.
What concepts are related to Product Quantization (PQ)?
Closely related concepts include ivf, ann, faiss.