LLM compression — 2 Technical Articles

Mar 31, 2026 · Artificial Intelligence

How Google’s TurboQuant Cuts KV‑Cache Memory by 83% and Boosts LLM Speed

Google’s newly released TurboQuant algorithm compresses KV‑Cache from 16‑bit to 3‑bit, slashing memory usage to one‑sixth while preserving zero accuracy loss, dramatically accelerating large‑language‑model inference on GPUs and reshaping the memory market.

AI inferenceGoogle ResearchKV cache

0 likes · 7 min read

How Google’s TurboQuant Cuts KV‑Cache Memory by 83% and Boosts LLM Speed

AI Code to Success

Mar 27, 2026 · Artificial Intelligence

How Google’s TurboQuant Cuts LLM Memory by 6× and Speeds Up Inference 8×

Google Research’s TurboQuant algorithm compresses large‑language‑model KV caches from 32‑bit to 3‑bit, achieving a six‑fold reduction in memory usage and an eight‑fold inference speedup on H100 GPUs while preserving 100 % accuracy, and it also improves vector search performance without requiring large codebooks.

AI EfficiencyInference AccelerationLLM compression

0 likes · 10 min read

How Google’s TurboQuant Cuts LLM Memory by 6× and Speeds Up Inference 8×