Choosing Between Frontier Models Without Wasting a Month

Public leaderboards measure broad capability. Your workload is narrow, repetitive and full of edge cases the benchmarks never see. That gap is why teams often pick a model, ship, and then quietly swap it three months later.

Start from the failure you cannot tolerate

Every deployment has one class of error that matters more than the rest: a factual slip in a medical summary, a hallucinated function call in code, a tone failure in customer messaging. Rank candidates by behaviour on that specific failure, not by aggregate scores.

A workable evaluation loop

• Collect 50 real examples. Pull them from production logs, support tickets or past projects rather than inventing test prompts.
• Define pass criteria in writing. "Good enough" without a written threshold produces arguments, not decisions.
• Score blind. Have reviewers see outputs without model labels.
• Measure cost per accepted output. A cheaper model that needs three retries is not cheaper.
• Re-run the set monthly. Model versions move faster than most release calendars.

Latency is a feature, not a footnote

Interactive products tolerate roughly two seconds before users notice delay. Batch pipelines tolerate minutes. The same model can be the right or wrong choice depending on which side of that line your product sits.

Keep the abstraction thin

Wrap calls behind a small internal interface so swapping a provider is a configuration change rather than a refactor. Teams that hard-code one vendor's request format pay for it every time a version is retired.