Effort is a dial for how much reasoning a model does before it answers. Set per model provider request, it controls the length of the thinking the model works through before it starts writing the response you see. That thinking is generated at inference time like everything else; the harness often hides it, but it's real work the model is doing.
Higher effort costs more and runs slower. The reasoning is emitted as tokens, billed as output tokens even when you never see them, and produced one token at a time — so turning effort up lengthens the wait before the answer arrives and adds to the bill. The trade is more deliberation against speed and cost.
Most harnesses expose effort as a small ladder:
| Level | What it's for |
|---|---|
| Low | Mechanical edits, lookups, well-specified changes with one clear path. |
| Medium | Everyday coding — the usual default. |
| High | Tricky bugs, design decisions, multi-step plans. |
| Max | The hardest problems, where a wrong answer is expensive to unwind. |
The symptom of getting it wrong cuts both ways. Set effort too low on a hard problem and you get a confident, shallow answer that skipped the reasoning the problem needed — it reads fine and is wrong in a way that costs you later. Set it to max for a one-line rename and you sit through a long think that produces nothing the lowest setting wouldn't have.
Match effort to the task, not the session. Turn it up for the part that's genuinely hard to reason about, and back down for the rote work around it.
Usage:
"It keeps botching this concurrency fix — I've re-explained it three times."
"Bump the effort up. That's a reasoning-heavy bug, and on the default setting it's not thinking long enough before it commits to an approach."