Zero-Shot vs Few-Shot Prompting

Zero-shot A zero-shot prompt describes the task without examples. It is efficient for familiar work with an unambiguous output contract. Start here to discover what the model already understands.

Few-shot Few-shot prompting adds representative input-output pairs. Use it when labels, tone, edge cases, or formatting are difficult to describe precisely. Examples should cover meaningful variation, not repeat the same easy case.

Avoid accidental rules Models may copy irrelevant details from examples. Make examples internally consistent, anonymize sensitive data, and state which traits should generalize.

Evaluate Test on cases unlike the examples. If performance collapses, the prompt may be memorizing surface patterns instead of applying the intended rule.