05Benchmark · updated 9 November 2026
Which AI model is the most reliable and makes things up the least?
How much a model really knows, and how often it guesses when it does not know something.
How to read it
- Each bar is the score of one model. The test consists of 3,000 questions on business, law, health and software, among other things, which the model has to answer from memory, without files or looking things up.
- Higher is better. The score is the share of correct answers minus the share of wrong answers. Saying you do not know does not count as wrong, so guessing costs points.
- Point at a bar for the details: how many answers are correct (higher is better) and how often the model makes something up when it does not know (lower is better).
What it means for you
A model that knows a lot is not yet a reliable assistant. If it guesses when in doubt, you get confident but wrong answers, and those hurt in customer questions and legal or financial texts. So do not only look at who has the most correct answers, but also at who most often dares to say it does not know. Which model fits depends on what a wrong answer costs you.
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A benchmark does not choose a model for you. We do.
Which model is best depends on your work, your data and what it may cost per month. In an AI Partnership we choose per use case, and switch when a better model comes out.
More on how we approach that: the AI Partnership.
Free to use: all benchmarks are licensed under CC BY 4.0. Reuse or quote them, crediting: NinA AI Benchmarks, nina-ai.nl/benchmarks.
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