Comparison
Few-Shot vs Zero-Shot
Few-Shot and Zero-Shot are both common AI/LLM terms but cover different ideas. Here is a quick side-by-side.
When you would reach for Few-Shot
When zero-shot quality is unstable or the output format is unusual.
Three (sentiment, label) pairs followed by a new sentence to classify.
When you would reach for Zero-Shot
Zero-Shot comes up when the question is fundamentally about prompting.
"Summarize this article in 2 sentences."
Frequently asked
What is the difference between Few-Shot and Zero-Shot?
Few-Shot: Few-shot prompting includes a small number of input-output examples directly in the prompt so the model can pattern-match without any fine-tuning. Zero-Shot: Zero-shot prompting asks the model to perform a task without showing any examples — only the instruction and the input. Modern instruction-tuned models do this well.
When should I use Few-Shot vs Zero-Shot?
When zero-shot quality is unstable or the output format is unusual. Zero-Shot applies when you are focused on prompting.
Are Few-Shot and Zero-Shot the same thing?
No. Few-Shot is prompting; Zero-Shot is prompting. They are related but address different parts of the AI stack.