Glossary · Evaluation

What is Confidence interval?

Confidence interval is an evaluation concept used to measure language model behaviour. It is part of the vocabulary teams use when they compare models, design prompts or review an AI system.

Definition

Confidence interval is an evaluation concept used to measure language model behaviour. It is part of the vocabulary teams use when they compare models, design prompts or review an AI system. The term is used in evaluation discussions, where precision matters: two teams can use the same word to mean slightly different things. In this glossary, confidence interval is treated as a practical concept rather than a formal specification.

Why it matters

Evaluation terms cover how capability, reliability and safety are measured. They matter because a benchmark score is only useful if you understand what the test measures and where it can mislead.

Example

Suppose you are comparing Firesearch Mini with another model for a production task. Confidence interval is one of the factors behind the numbers you see: Firesearch Mini lists a 32,768-token context window, costs $3.94 per million input tokens and scores 66.5 on TruthfulQA. Understanding the term helps you decide which of those differences actually matter for your workload.

How to evaluate it

  • Check whether confidence interval is defined the same way in the documentation you are reading.
  • Ask which measurement or trade-off the term is describing before comparing numbers.
  • Separate vendor claims from independently observed behaviour on your own data.
  • Write down the definition your team uses so reviews and evaluations stay consistent.

Related terms

Related guides

FAQ

What does Confidence interval mean?

Confidence interval is an evaluation concept used to measure language model behaviour. It is part of the vocabulary teams use when they compare models, design prompts or review an AI system.

Why does Confidence interval matter?

Evaluation terms cover how capability, reliability and safety are measured. They matter because a benchmark score is only useful if you understand what the test measures and where it can mislead.

How is Confidence interval used in practice?

Suppose you are comparing Firesearch Mini with another model for a production task. Confidence interval is one of the factors behind the numbers you see: Firesearch Mini lists a 32,768-token context window, costs $3.94 per million input tokens and scores 66.5 on TruthfulQA. Understanding the term helps you decide which of those differences actually matter for your workload.