Google Research recently revealed TurboQuant, a compression algorithm that reduces the memory footprint of large language ...

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

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

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 unveils TurboQuant, PolarQuant and more to cut LLM/vector search memory use, pressuring MU, WDC, STX & SNDK.

The technique reduces the memory required to run large language models as context windows grow, a key constraint on AI ...

Google introduced an algorithm that it says improves memory usage in AI models. Whether that will actually eat into business for Micron and rivals is unclear. Micron's stock was down about 3% on ...

Memory stocks fell Wednesday despite broader technology sector strength, with shares dropping after Google unveiled TurboQuant, a new compression algorithm that could reduce memory requirements for AI ...

Memory stocks declined Wednesday as investors reacted to Google’s announcement of TurboQuant, a new compression algorithm ...

Broadcom is padding post-quantum security with its Emulex SecureHBA adapters now integrated into Everpure’s FlashArray ...

The algorithm achieves up to an eight-times performance boost over unquantized keys on Nvidia H100 GPUs.

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