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    How to read an AI benchmark table without fooling yourself

    Eight questions to ask before you trust a row on a leaderboard: who ran it, which version, under what settings, whether the benchmark still separates models, whether the model has seen it, what the grader checks, how big the noise is, and which harness produced it.

    7 min readEvaluation, Large language models, Agents

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