Google’s new TurboQuant algorithm speeds up AI memory 8x, cutting costs by 50% or more
Carl Franzen March 25, 2026 Credit: VentureBeat made with Google Gemini 3.1 Pro ImageAs Large Language Models (LLMs) expand their context windows to process massive documents and intricate conversations, they encounter a brutal hardware reality known as the “Key-Value (KV) cache bottleneck.”Every word a model processes must be stored as a high-dimensional vector in high-speed memory. For long-form tasks, this “digital cheat sheet” swells rapidly, devouring the graphics processing unit (GPU) video random access memory (VRAM) system used during inference, and slowing the model performance down rapidly over time. But have no fear, Google Research is here: yesterday, the unit within the search giant released its TurboQuant algorithm suite — a software-only breakthrough that provides the…
