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A common practice is to first use public indices to shortlist candidate models, then build a small-scale private evaluation set (such as 50-200 real samples) targeting one's own high-frequency business tasks, scoring comprehensively on three metrics—task accuracy, cost and latency—and retesting regularly to cope with behavioral drift caused by model version updates.
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10/29/2026
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