Which layers should stay in higher precision after quantization, and how do you find them with a sensitivity sweep?
A few matrices cause most of the damage when a model is quantized, and keeping them wide costs little memory. The answer builds the sweep that finds them, prices it in GPU hours, and explains why the sum of single-layer damages is not the damage of the mix.
Updated Oct 2026 · Worked answers on inference mechanisms, with calculations, implementation details, and follow-up questions.
A few matrices cause most of the damage when a model is quantized, and keeping them wide costs little memory. The answer builds the sweep that finds them, prices it in GPU hours, and explains why the sum of single-layer damages is not the damage of the mix.
At batch 1 the step reads every weight once to produce one token per sequence, so arithmetic intensity sits near 1 FLOP per byte and the tensor cores idle.