matryoshka

A single trained embedding you can cut to any length and still use. The signal is the nested-prefix training objective and the coarse-to-fine retrieval win it enables at scale. Here is the answer.

float32 is far more precision than ranking needs. int8 is close to free, binary is 32x smaller, and the difference between a working binary index and a recall disaster is one word: rescoring.