Advanced Concepts
Reasoning model
A model optimized to spend more computation working through difficult problems before answering.
Example
A reasoning model spends additional computation working through a difficult planning problem.
Why it matters
It can improve performance on tasks that benefit from checking several steps before answering.
You'll hear it
“This problem needs more than a quick first guess.”
Can you control it?
Not directly
No, not directly. A reasoning model describes a learned property, observed result, or broader concept rather than a normal user setting. You may influence it indirectly by changing the tool, data, prompt, or workflow.
Common questions
- Does it always beat a faster model?
- No. Simple tasks may gain little, and a stronger reasoning setup can still make mistakes.
- Can it solve a problem with missing facts?
- Not reliably. More processing does not supply facts that the system has no way to obtain.
- Should I trust its explanation as proof?
- No. Check the conclusion and evidence; a convincing explanation can still support a wrong answer.