AI glossary · Building and running AI
AI benchmark
An AI benchmark is a standard test used to measure and compare how well AI models perform on a task, such as maths problems, coding or general knowledge.
Also called benchmark, leaderboard
In more detail
AI companies report benchmark scores when they release new models, and public leaderboards rank models by them. They are useful for rough comparisons.
Scores don’t always reflect real-world usefulness: models can be tuned to specific tests, and test questions sometimes leak into training data. Your own tests, often called evals, are a better guide for a specific job.
Related terms
AI evalsAI evals are repeatable tests that check whether an AI feature gives good results, using set inputs and clear scoring rules.Frontier modelA frontier model is one of the most advanced AI models available at a given time, the kind that pushes the limits of what AI can do.Turing testThe Turing test, proposed by Alan Turing in 1950, asks whether a machine can hold a text conversation that people can’t tell apart from a human’s.DatasetA dataset is an organised collection of data, such as a table of house prices or a folder of labelled photos, used to train or test AI models.
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