PromptSharpGlossary › Self-Consistency

What is Self-Consistency?

Self-consistency runs a reasoning prompt several times and takes the most common answer, improving reliability on hard problems.

Self-consistency is a technique that pairs with chain-of-thought: instead of trusting a single reasoned answer, you generate several independent attempts (often at a higher temperature) and take the answer that appears most often. Correct reasoning tends to converge; one-off errors don't.

It costs more (multiple generations) but meaningfully improves accuracy on math and logic. A lightweight manual version: ask the model to solve a hard problem three different ways and reconcile any disagreement.

Frequently asked

How is self-consistency different from just asking once?

Asking once gives you whatever single path the model took, errors included. Self-consistency samples several independent reasoning paths and takes the majority answer, filtering out one-off mistakes at the cost of extra generations.

Related terms

Put this into practice

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Reality guardrail: definitions here are practical, not academic. AI models predict likely text, not verified truth — always check names, numbers, and citations against a trusted source before you rely on an answer.

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