I spent 31 hours on the math behind TurboQuant so you don't have to

This post provides a deep dive into the mathematical principles behind TurboQuant, a novel quantization technique for LLM KV caches. It explains the KV cache problem, existing quantization methods like NVFP4, and the theoretical basis for TurboQuant's approach using random preconditioning and polar transformations. The post includes code examples and mathematical derivations to illustrate how TurboQuant manipulates data to achieve tighter distributions and reduce memory footprint, aiming for significant compression of KV cache data.