Zero-Shot Prompting
Simple Definition
Zero-shot prompting means giving an AI a task with no examples — just an instruction. The model uses only what it learned during training to figure out what you want and how to respond.
“Zero-shot” means zero examples. Most everyday AI use is zero-shot: you type a question or request and the AI responds without you providing any sample answers first.
Example
Zero-shot prompt:
Summarize the following article in 3 bullet points: [article text]
No examples are provided. The model already knows what “summarize” means and what bullet points look like from its training.
When Zero-Shot Works Well
Zero-shot works well for:
- Common, well-understood tasks (summarizing, translating, explaining)
- Tasks where quality doesn’t need to exactly match a specific format
- Quick, one-off requests where adding examples would take too long
When to Switch to Few-Shot
Use few-shot prompting when:
- You need a very specific output format
- The model’s zero-shot attempts keep missing the mark
- The task is unusual or highly specialized
- Consistency across many outputs is important
The Spectrum of Shots
| Type | Examples in Prompt |
|---|---|
| Zero-shot | 0 |
| One-shot | 1 |
| Few-shot | 2–5 |
| Many-shot | 10+ |
Modern LLMs are surprisingly capable at zero-shot tasks — which is what makes them so useful without any setup.
Related Terms
- Few-Shot Prompting — providing examples to guide the model
- Prompt Engineering — the skill of writing effective prompts
- Chain-of-Thought — a technique for complex reasoning tasks
- LLM — models capable of zero-shot task completion
See AI terms in action
Browse practical AI workflows that use the concepts in this glossary.
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