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Reasoning Effort & Adaptive Thinking

🧠 Reasoning Models 12 min 300 BASE XP

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

LevelThinking TimeCostBest For
low~1-2sLowestSimple classification, quick answers
medium~3-5sModerateStandard coding, analysis
high~5-30sHighestComplex math, architecture design, research

GPT-5.4 Adaptive Reasoning

GPT-5.4 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: "gpt-5.4",
  input: "What is 2+2?"  // Instant response, no deep thinking
});

// Force deep reasoning:
const complex = await openai.responses.create({
  model: "gpt-5.4",
  reasoning: { effort: "high" },
  input: "Design a distributed consensus algorithm for a 10-node cluster"
});
💡 Cost Tip: Let GPT-5.4 use adaptive reasoning by default. Only set explicit effort levels when you know the task complexity upfront.
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
Watch: 139x Rust Speedup
Reasoning Effort & Adaptive Thinking | Reasoning Models — OpenAI Academy