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.

Running a large language model is expensive, and a surprising amount of that cost comes down to memory, not computation.

VerTQ is an accelerator chip that implements Google's TurboQuant algorithm which reduces KV cache memory usage of Large ...

We have seen the future of AI via Large Language Models. And it's smaller than you think. That much was clear in 2025, when ...

If Google’s AI researchers had a sense of humor, they would have called TurboQuant, the new, ultra-efficient AI memory compression algorithm announced Tuesday, “Pied Piper” — or, at least that’s what ...

Highflying memory stocks like Micron and SanDisk have been dented this week and it might have something to do with TurboQuant, a compression algorithm detailed by Google in a research paper this week.

At its core, the TurboQuant algorithm minimizes the space required to store memory while also preserving model accuracy. To the casual observer, TurboQuant looks like a software shortcut that allows ...

Google Research released TurboQuant, a training-free compression algorithm that can compress the KV cache of large language models (LLM) to 3 bits without affecting model accuracy,... Google Research ...

Even if you don’t know much about the inner workings of generative AI models, you probably know they need a lot of memory. Hence, it is currently almost impossible to buy a measly stick of RAM without ...