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.

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 ...

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 ...

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.

The compression algorithm works by shrinking the data stored by large language models, with Google’s research finding that it can reduce memory usage by at least six times “with zero accuracy loss.” ...

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 sent shockwaves through a small corner of the artificial intelligence (AI) market when it released new research that could significantly impact certain chipmakers. The Alphabet (NASDAQ: GOOG) ...

Google Research's TurboQuant memory-compression algorithm has raised concerns that demand for AI-related memory could weaken, but South Korean experts and analysts say the market reaction may be ...