I’m comparing OpenAI model settings for a feature that needs to explain its decisions, but not every request needs deep reasoning. How much do reasoning effort settings change response time and token cost in real workloads?

If you’ve tested this in production, what kinds of tasks showed a meaningful quality difference, and how did you decide where the extra latency was worth it?