Breaking end-to-end latency into explicit stages gives teams a much better chance of improving real performance instead of optimizing the wrong layer.

1. Measurement strategy Use a fixed input set, record timestamps at every stage boundary, and repeat enough runs to separate warm-up behavior from steady-state performance.

2. Common surprises Preprocessing and data movement often dominate more than expected once the model itself is already well optimized on the accelerator.