Google Research unveiled TurboQuant, a novel quantization algorithm that compresses large language models’ Key-Value caches ...
Large language models (LLMs) aren’t actually giant computer brains. Instead, they are massive vector spaces in which the ...
TurboQuant vector quantization targets KV cache bloat, aiming to cut LLM memory use by 6x while preserving benchmark accuracy ...
Within 24 hours of the release, community members began porting the algorithm to popular local AI libraries like MLX for Apple Silicon and llama.cpp.
Google researchers have proposed TurboQuant, a two-stage quantization method that, according to a recent arXiv preprint, can ...