ModelRefs / Self-Consistency — AI Glossary
Self-Consistency — AI Glossary
A decoding strategy that samples multiple chain-of-thought reasoning paths and majority-votes the final answer.
Overview
Self-consistency (Wang et al., 2022) yields substantial gains on math and reasoning benchmarks at the cost of N× tokens and latency. Reduces sensitivity to unlucky single-sample reasoning paths.
Reference details
| Topic | reasoning |
|---|---|
| Last reviewed | 2026-06-24 |
Related terms
Commonly confused with
Like tree of thoughts, this samples more than one reasoning path — but it never evaluates or prunes them. It generates several independently and takes the majority answer, which makes it far cheaper and means it needs answers that can be compared for equality. That works for a number or a label and does not work for an essay, where there is no majority to take.
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Frequently asked questions
What is Self-Consistency?
A decoding strategy that samples multiple chain-of-thought reasoning paths and majority-votes the final answer.
What concepts are related to Self-Consistency?
Closely related concepts include chain of thought, tot, reasoning model.