Self-consistency
Self-consistency is a technique that samples several independent answers to the same prompt and takes the most common result, instead of trusting a single response.
It trades cost for reliability and works best where answers are discrete enough to compare — a number, a category, a yes or no. It costs as many model calls as samples taken, so it suits verification steps rather than every request.
Related terms
- Chain-of-thought prompting
- Chain-of-thought prompting is instructing a model to work through its reasoning step by step before giving an answer, rather than answering immediately.
- LLM as judge
- LLM as judge is using one language model to grade another model’s output against a written rubric.
More on techniques
See the full glossary, read the guides, or put it into practice in the prompt builder.