At each step a model assigns probabilities to possible next tokens. Temperature reshapes that distribution before sampling: near 0, the most likely token almost always wins; higher values give less likely tokens more chance.
Use low temperature for extraction and factual tasks, higher for brainstorming. Related settings include top-p and top-k sampling.