The biggest memory burden for LLMs is the key-value cache, which stores conversational context as users interact with AI ...
Within 24 hours of the release, community members began porting the algorithm to popular local AI libraries like MLX for ...
Google has published TurboQuant, a KV cache compression algorithm that cuts LLM memory usage by 6x with zero accuracy loss, ...
Google's TurboQuant algorithm compresses LLM key-value caches to 3 bits with no accuracy loss. Memory stocks fell within ...
The algorithm achieves up to an eight-times performance boost over unquantized keys on Nvidia H100 GPUs.