[ ABORT TO HUD ]
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Reasoning Effort & Adaptive Thinking
Calibrating Reasoning Depth
The reasoning effort parameter lets you control how much time the model spends thinking. This is a cost-quality tradeoff.
Effort Levels
| Level | Thinking Time | Cost | Best For |
|---|---|---|---|
| low | ~1-2s | Lowest | Simple classification, quick answers |
| medium | ~3-5s | Moderate | Standard coding, analysis |
| high | ~5-30s | Highest | Complex math, architecture design, research |
OpenAI o3-mini Adaptive Reasoning
OpenAI o3-mini models feature adaptive reasoning - they automatically decide whether to think deeply or respond instantly based on query complexity. You can override this with explicit effort settings.
// Let the model decide how much to think:
const simple = await openai.responses.create({
model: "o3-mini",
input: "What is 2+2?" // Instant response, no deep thinking
});
// Force deep reasoning:
const complex = await openai.responses.create({
model: "o3-mini",
reasoning: { effort: "high" },
input: "Design a distributed consensus algorithm for a 10-node cluster"
});
💡 Cost Tip: Let OpenAI o3-mini use adaptive reasoning by default. Only set explicit effort levels when you know the task complexity upfront.
⌨ HANDS-ON LABCalibrate Reasoning Effort Levels
⭐ +200 XPControl reasoning budget and inference latency on o3-mini. Submit a request with reasoning_effort set to high.
1POST to /v1/chat/completions with reasoning_effort set to high on o3-mini.
OBJECTIVE 1 / 1 — type "hint" if stuck
SYNAPSE VERIFICATION
QUERY 1 // 3
What does the reasoning effort parameter control?
Model temperature
How much time and compute the model spends thinking before answering
The number of tokens generated
Network latency