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.

Large language models (LLMs) aren’t actually giant computer brains. Instead, they are massive vector spaces in which the probabilities of tokens occurring in a specific order is encoded. Billions of ...

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

AI has a growing memory problem. Google thinks it's found the answer, and it doesn't require more or better hardware. Originally detailed in an April 2025 paper, TurboQuant is an advanced compression ...

Google's TurboQuant can dramatically reduce AI memory usage. TurboQuant is a response to the spiraling cost of AI. A positive outcome is making AI more accessible by lowering inference costs. With the ...

Google LLC has unveiled a technology called TurboQuant that can speed up artificial intelligence models and lower their memory requirements. Amir Zandieh and Vahab Mirrokni, two of the researchers who ...

In March 2026, Google Research announced ' TurboQuant ' as one of a new suite of compression technologies for large-scale language models and vector search engines. To visually understand what ...

Google's TurboQuant reduces the KV cache of large language models to 3 bits. Accuracy is said to remain, speed to multiply. Google Research has published new technical details about its compression ...

AI just found a way to use less memory. That does not mean memory will get cheaper. Google’s new technique, TurboQuant, is generating buzz for dramatically reducing how much memory AI models need ...