Reasoning effort controls how much internal processing a reasoning-capable model uses for a task. Higher effort can help with difficult debugging, planning or analysis, but it may also increase latency and cost.
The setting should match the evidence about task difficulty. Routine work can begin at a moderate level, while a specific problem that resists a clear prompt and normal investigation may justify additional effort.
ELI5
Reasoning effort is a control for how much work an AI model does before answering. It is similar to choosing between a quick mental estimate and sitting down to work through a problem step by step.
For example, a low setting might be enough to rename a variable in a small code sample, while a complex bug across many files may need more effort. More effort can take longer and cost more, and it still does not guarantee the right answer.
Does higher reasoning effort always produce a better result?
No. Extra computation can waste time and cost on straightforward tasks, and it cannot replace missing evidence or unclear requirements.
When should reasoning effort be increased?
Increase it when a clearly described, well-evidenced problem remains difficult after an appropriate prompt and normal checks.
