Find the thinking level
that earns its cost.

No. Some published sweeps show a lower score at a higher effort. For example, GPT-6 Sol scores 61.3 at extra high and 57.0 at max in Hex DataBench v1.1. That is a 4.3-point observed decline in this analytics harness. It does not prove that max is worse on every task.

Choose a matching benchmark and task measure first. LiveBench offers coding, research and other task-weighted profiles; OckBench separates math, coding and science; DataBench covers analytics agents. Our near-best pick selects the lowest measured cost, otherwise lowest measured output tokens, otherwise lowest tested effort within your allowed score gap. Validate the shortlist on your own tasks.

Xhigh means extra high reasoning effort. It asks a supported model to invest more effort than high, but it is not a fixed token budget. Available settings and defaults depend on the model, provider and tool. The same label is not a comparable quantity across providers.

It depends on the benchmark, task count and repeatability. We call gaps under 1 point small, 1 to under 5 noticeable, and 5 or more large as a reading aid. Those labels and the default 1-point tolerance are editorial choices, not statistical significance tests. The sources generally do not supply per-mode confidence intervals.

Only explicitly identified, published configurations enter a sweep. Missing modes are not estimated, and unknown defaults are excluded. We show dollar costs or duration only when the same source measured them. Output tokens alone cannot determine the full bill.

Yes. The measured-cost calculator scales the average cost of a benchmark task. The separate reasoning-token calculator uses your own token assumptions and editable input/output prices. A mode label alone cannot predict its token usage, cost or score on your workload.