Can I trust AI benchmark scores?
Treat a benchmark score as a lead to check, not a verdict. It describes performance on fixed tasks under stated conditions, vendor-reported scores are claims, and public test questions can leak into training data. Look for who ran the test, the conditions, the version and the date.
The full answer
Treat a benchmark score as a lead to check, not a verdict. A benchmark is a fixed set of tasks with a scoring rule, so a score describes performance on those tasks under those conditions, not on your work. Scores a vendor publishes about its own model are vendor-reported claims, and different vendors use different harnesses, effort settings and tools, which makes numbers from different pages hard to compare.
Public question sets can also leak into training data, a problem called benchmark contamination, so a high score may reflect memorization. Look for who ran the test, the conditions, the product version and the date.
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