Zero-shot prompting gives only instructions, while few-shot prompting includes examples of the desired input-output behavior.

Few-shot examples help the model infer style, structure, edge cases, and label definitions. They are useful when the task is ambiguous or format-sensitive, but they consume context and can bias the model.