At each step, model outputs a probability distribution over vocabulary, samples a token, appends it to context, repeats.

At each step, model outputs a probability distribution over vocabulary, samples a token, appends it to context, repeats. Temperature scales the distribution (lower = more deterministic). Top-k samples only from the k highest-probability tokens. Top-p (nucleus sampling) samples from the smallest set whose cumulative probability ≥ p — adapts dynamically, preferred over fixed top-k.