ModelRefs / Zero-Shot Prompting — AI Glossary
Zero-Shot Prompting — AI Glossary
Prompting a model to perform a task without providing any example input-output pairs. Zero-shot works well with frontier models on most standard tasks.
Overview
Zero-shot works well with frontier models on most standard tasks. It fails on tasks with idiosyncratic output formats or niche domain knowledge where examples (few-shot) or retrieved context (RAG) are needed.
Reference details
| Topic | prompting |
|---|---|
| Last reviewed | 2026-06-24 |
Related terms
Commonly confused with
The contrast with few-shot, and the default has flipped. Instruction-tuned models frequently do better with a clear zero-shot instruction than with examples, because badly chosen examples teach format quirks and narrow the model's interpretation of the task. Few-shot still wins when the output format is hard to describe but easy to demonstrate. Test both rather than assuming examples help.
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Frequently asked questions
What is Zero-Shot Prompting?
Prompting a model to perform a task without providing any example input-output pairs.
What concepts are related to Zero-Shot Prompting?
Closely related concepts include few shot, chain of thought, prompt engineering.