AI Memory Down From 42GB to 7GB. Here’s What Google’s TurboQuant Actually Did.

Google’s TurboQuant compresses LLM memory by 6x with zero accuracy loss. Here’s what that actually means for your infrastructure bill - and what to do about it today. Image generated by AI If you’ve ever tried to self-host a large language model, you’ve run into the wall. Not the model weights - those are manageable. A 70B model in 16-bit precision takes around 140GB of VRAM. Heavy, but knowable. The thing that quietly destroys your GPU budget is something most developers don’t think about until it’s already the problem: the KV cache.