What does Sampling parameters mean in inference serving?
Sampling parameters reshape the next-token distribution after model logits are computed. Temperature changes score sharpness, while nucleus sampling restricts choices to a selected probability mass. Benchmarks disclose sampling and stopping settings alongside prompt and output lengths. Teams attribute speed differences to measured work instead of assuming a parameter changes model computation.