What is reasoning effort?

How the setting works

A reasoning model writes a chain of intermediate steps before the final answer. The effort level sets a budget or a bias for that chain. At low effort the model answers with less deliberation; at high effort it explores more, checks more and writes more.

The names differ by vendor. Codex CLI takes an effort value per request. Claude Code takes an effort flag; when the flag is not passed, the CLI chooses, and we call that default. Default is not the same as medium, and its level is not published, so our charts place it after the named levels.

Does more effort buy quality?

Not on our hard set. In the effort ladder study, three models ran 8 hard tasks with strict validators, twice each, at every effort:

• All 11 configurations (Sonnet 5.5 at low, medium, high and default; Opus 5.5 at the same four; GPT-6.1 Sol through the Codex CLI at low, medium and high) passed 16 of 16 calls strictly.
• Each 16/16 has a 95% Wilson interval of 81% to 100%.
• There were 0 format misses and 0 wrong answers in 176 calls.

So pass rate does not separate any effort level here. The set has a ceiling for these models: with 16 calls per cell it cannot rule out a difference of up to about 19 points. "No difference found" is not "no difference".

What more effort did change

More effort changed output and time. Median total time per call:

• Sonnet 5.5: low 5.8 s, medium 7.6 s, high 8.8 s, default 8.0 s.
• Opus 5.5: low 7.5 s, medium 9.7 s, high 10.1 s, default 9.2 s.
• GPT-6.1 Sol (Codex CLI): low 13.6 s, medium 13.1 s, high 18.1 s.

Within each model the fastest and slowest calls of every effort overlap, so these medians describe this run; they are not a tested ranking. Median output tokens for Sonnet went from 667 at low to 770 at medium and 1,192 at high.

What it costs per correct answer

At list price (a calculation; the calls ran on subscriptions), the cost per strict pass went from:

• $0.0122 at low to $0.0167 at high for Sonnet 5.5,
• $0.0212 at low to $0.0337 at high for Opus 5.5,
• $0.0128 at low to $0.0151 at high for GPT-6.1 Sol through the Codex CLI.

Cost does not always rise in order: for GPT-6.1 Sol the medium cell cost more per pass than the high cell in this run. Per-call cost depends on output length, which varies from call to call.

How to choose an effort level

• Start low on tasks your model already passes. If low passes, a higher effort only adds time and cost.
• Raise effort when you see failures that look like reasoning errors, not format errors. Fix the format first; a correct answer in the wrong format is a validator problem.
• Measure on your own hard cases. Our set has a ceiling for these models. Your hardest tasks may not.
• Compare like with like. Change only the effort: same model, same route, same tasks, same validators. Otherwise you measure several things at once.
• Count every call. A higher effort that times out more often must show those failures in its rate.

Frequently asked questions

Is high reasoning effort always better?

No. On our 8 hard tasks, every effort level of Sonnet 5.5, Opus 5.5 and GPT-6.1 Sol passed 16 of 16 calls, so high effort bought no measurable quality there. It did raise median time per call and the list-price cost per pass.

What does "default" effort mean in Claude Code?

It means the effort flag was not passed, so the CLI chose the level. Its level is not published, so we report it as its own configuration and do not treat it as medium.

How much slower is high effort than low?

In our run, Sonnet 5.5 went from a median 5.8 s per call at low to 8.8 s at high, and Opus 5.5 from 7.5 s to 10.1 s. The ranges of single calls overlap, so the gap is not a tested ranking.

How many calls do I need to see an effort difference?

More than 16 per cell when both sides score near 100%. At 16/16 the 95% interval still reaches down to 81%, so a real difference smaller than about 19 points could hide inside it. Harder tasks, where the models fail sometimes, separate effort levels with fewer calls.