TurboQuant

lastmod 2026-07-19created 2026-07-191 edits

TurboQuant is a two-stage vector quantization algorithm developed by Google to solve the KV cache memory bottleneck that occurs when large language models (LLMs) process long contexts. It can compress memory usage to around 3–4 bits, nearly 6x, without losing the accuracy of high-dimensional vectors.

See also

• L2 normalization

Favorite site

• Understanding TurboQuant through visualization - YouTube