Unverified60% confidenceSolutionExact time
The most reliable model evaluation practice is to build a private evaluation benchmark based on one's own real business data.
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9/12/2026
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UnverifiedA more reliable approach when evaluating large language models is to build a domain-specific evaluation set strongly relevant to one's own business and conduct blind comparative testing on a real input distribution.79% similarUnverifiedLeaderboard scores are based on public test sets, and a model's actual performance on one's own business data still needs to be verified independently.77% similarUnverifiedWhen evaluating models, enterprises should establish an internal task benchmark set and use real business samples for regression testing rather than relying on general leaderboards published by vendors.73% similarUnverifiedThe key to the evaluation stage is building evaluation sets from real business data, rather than relying solely on public leaderboard scores.73% similarUnverifiedWhen evaluating model capabilities, attention should be paid to specific evaluation methods and datasets, with vigilance against the one-sidedness of single metrics and emphasis on independent third-party verification.72% similar
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