Model selection gets easier when you stop shopping for the highest score and start defining the work. Use this checklist before you compare vendors, plans, or benchmark tables.
Write down the task boundary
Name the inputs, the expected output, and what a good result looks like. “Help with research” is vague; “summarize a 30-page PDF and cite every claim” can be tested.
- What must the model do? List three representative tasks.
- What can never go wrong? Identify costly, unsafe, or embarrassing failures.
- How much context is typical? Measure real inputs rather than edge cases.
- Which tools must connect? Include files, search, code, and business systems.
- How fast must it respond? Set an acceptable latency range.
- What is the cost ceiling? Price a successful task, not a single token.
- Who reviews the output? Define where human judgment remains essential.
Shortlist, then test
Choose two or three candidates that meet the hard requirements. Run the same representative cases through each, score the outputs blind when possible, and document recurring failure patterns. A modest evaluation built from your work is more useful than a giant public leaderboard.
Keep the decision reversible
Models change quickly. Avoid unnecessary lock-in, keep prompts portable, and repeat your evaluation when a provider ships a meaningful update. The best choice this quarter may become the runner-up next quarter.
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