Capability-Matched Cost Cutting: Pay for the Ceiling You Use
The most common AI budget mistake is paying flagship prices for work a mid-tier model does identically. Summaries, extractions, reformatting, first drafts: on tasks like these, models thirty points apart on price are often indistinguishable in output. The fix is not "use cheaper models". It is matching the capability ceiling you pay for to the ceiling the task actually touches.
Read the two numbers together
Every benchmarked model in the catalog carries a capability index (0 to 100, fit over 50+ public benchmarks) and a blended list price per 1M tokens. Read alone, either number misleads: the cheapest model is weak, the strongest is expensive. Read together they form a frontier, and the capability-per-dollar view plots it: the models on the frontier line are the ones nothing beats on both numbers at once. Anything far above the line is a candidate for replacement.
Find the swap, then verify it
For a specific model you use today, the savings finder does the mechanical part: pick your model and a capability tolerance, and it lists every model within range that lists cheaper, with both numbers visible. The index is not task-specific, so treat the list as candidates, not verdicts. Verification is one step: run your three most representative prompts through a side-by-side comparison of the current model and the candidate, and read the outputs blind. If you cannot tell which is which, the decision made itself.
Route by task, not by loyalty
The durable version of this is a routing habit. Keep a flagship for the work that earns it: multi-step reasoning, subtle rewriting, anything where a wrong answer is expensive. Send the bulk lane (summarize, extract, classify, translate) to a model from the cheapest board that clears your quality bar. In idapt the switch is a per-chat model pick or an agent default, so the routing lives in your setup rather than your discipline. The auto-router does a version of this for you when you let it: how it picks is documented.
Recheck quarterly
Prices move and new models land weekly (the release timeline tracks both). A swap that was wrong in April is often right by July, so put a fifteen-minute recheck on the calendar: rerun the savings finder on your two most-used models and re-verify anything new inside your tolerance. Cost cutting that survives is a cadence, not an event.
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