Large language models (LLMs) aren’t actually giant computer brains. Instead, they are massive vector spaces in which the ...

TurboQuant vector quantization targets KV cache bloat, aiming to cut LLM memory use by 6x while preserving benchmark accuracy ...

What Google's TurboQuant can and can't do for AI's spiraling cost ...

On March 24, 2026, Google Research announced a new suite of compression techniques for large-scale language models and vector search engines: TurboQuant, PolarQuant, and Quantized ...

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.

Learn why Google’s TurboQuant may mark a major shift in search, from indexing speed to AI-driven relevance and content discovery.

A new quantum sensing approach could dramatically improve how scientists measure low-frequency electric fields, a task that ...

This is really where TurboQuant's innovations lie. Google claims that it can achieve quality similar to BF16 using just 3.5 ...

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 ...

Google has unveiled a new AI memory compression technology called TurboQuant, and the announcement has already had a measurable impact on the semiconductor market. The technology is designed to reduce ...

Google’s TurboQuant has the internet joking about Pied Piper from HBO's "Silicon Valley." The compression algorithm promises ...