
TurboQuant compression could slash KV cache costs for LLMs
On March 24, 2026, Google Research introduced TurboQuant, a family of quantization methods built to shrink large language model artifacts and vector indexes without the usual overhead that blunts gains. In its announcement, Google frames TurboQuant as “theoretically grounded” and designed for both LLM serving and vector search. The pitch is simple: TurboQuant compression aims […]







