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.

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 ...

TurboQuant launch: Google’s new algorithm slashes AI computing costs, enabling faster, more efficient semantic search and instant indexing. SEO strategy shift: Marketers must prioritize building ...

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 ...