The biggest memory burden for LLMs is the key-value cache, which stores conversational context as users interact with AI chatbots. The cache grows as conversations lengthen, ...
Google thinks it's found the answer, and it doesn't require more or better hardware. Originally detailed in an April 2025 paper, TurboQuant is an advanced compression algorithm that’s going viral over ...
As 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 ...
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Google's TurboQuant reduces AI LLM cache memory capacity requirements by at least six times
The algorithm achieves up to an eight-times performance boost over unquantized keys on Nvidia H100 GPUs.
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