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

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A paper from Google could make local LLMs even easier to run.

Memory prices are softening after Google figured out a way to make memory usage more efficient. Is this the death knell for ...

So far, so futile. Both these approaches are doomed by their respective medium being orders of magnitude slower to access and ...

Is increasing VRAM finally worth it? I ran the numbers on my Windows 11 PC ...

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

Macworld explains that chip binning is Apple’s practice of disabling faulty cores in processors to create different ...

Turbo Quant Doesn't Impact DIMM Count If compression doesn't cross a DIMM boundary, it has zero hardware impact The Market Overreaction Google's TurboQuant has triggered a sharp reaction across ...

Apple Inc. Buy: discover how unified memory, on-device AI, and privacy drive Mac demand and high-margin services—I see ...

Google researchers have published a new quantization technique called TurboQuant that compresses the key-value (KV) cache in large language models to 3.5 bits per channel, cutting memory consumption ...

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 algorithm that’s going viral over ...