TurboQuant: What Developers Need to Know About...

If you've ever run a large language model on your own hardware and watched your GPU memory vanish as the context window grows, TurboQuant is built for exactly that problem. Published by Google Research on March 24, 2026 and headed to ICLR 2026, TurboQuant is a compression algorithm that shrinks the KV cache -- the biggest memory bottleneck during LLM inference -- down to 3-4 bits per element without any retraining or fine-tuning. The result is roughly a 4-6x reduction in KV cache memory with neg