Google introduces TurboQuant, cutting LLM memory usage by 6x with no accuracy loss

The biggest memory burden for LLMs is the key-value cache, which stores conversational context as users interact with AI ...

Google's new TurboQuant algorithm speeds up AI memory 8x, cutting costs by 50% or more

Within 24 hours of the release, community members began porting the algorithm to popular local AI libraries like MLX for ...
WinBuzzer

Google’s TurboQuant Algorithm Slashes LLM Memory Use by 6x

Google has published TurboQuant, a KV cache compression algorithm that cuts LLM memory usage by 6x with zero accuracy loss, ...
The Next Web

Google’s new compression algorithm cut memory stocks within hours of publication

Google's TurboQuant algorithm compresses LLM key-value caches to 3 bits with no accuracy loss. Memory stocks fell within ...
SDxCentral

TurboQuant: Did Google just drop a compression algorithm capable of stemming RAMageddon?

Google thinks it's found the answer, and it doesn't require more or better hardware. Originally detailed in an April 2025 ...

TurboQuant: Google aims to curb the memory hunger of large LLMs

Google's TurboQuant reduces the KV cache of large language models to 3 bits. Accuracy is said to remain, speed to multiply.
Tom's Hardware on MSN

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.