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CHOOSING-AI-MODELS5 MIN READ

Quick Reference: Benchmark Cheat Sheet

Recall the practical rules for using benchmark results responsibly in model selection.

What is a benchmark result strongest at telling you? It tells you how a model performed on a specific task family, dataset, and scoring rule. That is enough to update your shortlist or pilot plan. It is not enough to skip local evaluation. SWE-bench vs MMMU Different benchmarks answer different model-selection questions. A model that wins on one may deserve a pilot in the overlapping workflow, not automatic dominance everywhere else. Objection handling “The model is number one, so why are we still testing it?” A stakeholder wants to move fast from external evidence to internal standardization. Answer Because rank…

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