Google invents TurboQuant to shrink AI data without losing accuracy

Google researchers developed TurboQuant, a compression method that reduces high-dimensional vectors and key-value pairs in AI models without accuracy loss or extra memory overhead. It resolves key-value cache bottlenecks, enabling faster similarity searches and lower costs for search and long-context tasks. Presented at ICLR 2026.