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Last updated: April 19, 2026, 8:30 AM ET

LLM Memory Optimization

Google researchers developed TurboQuant to address the massive VRAM consumption caused by the Key-Value (KV) cache in large language models. This novel quantization framework employs a multi-stage compression pipeline utilizing Polar Quant and QJL techniques to achieve near-lossless storage efficiency, directly combating memory bottlenecks that limit deployment scale.