Temperature is a model setting that controls how random or deterministic generated output should be. Lower temperatures usually produce more predictable text. Higher temperatures usually produce more varied text in prompting workflows.
What it changes
- Predictability.
- Variety.
- Chance of surprising wording.
AEO rule of thumb
Predictable output is usually better when the page needs to be represented accurately. If the task is to preserve facts, a low-temperature setting usually makes more sense than a creative one and helps reduce hallucination.
Example:
Ajey uses a low temperature setting for an AwesomeShoes Co. product summary because he wants the model to stay close to the source facts. If he raises the temperature too much, the output may become more varied, but it can also drift away from the actual product details.
The useful boundary is simple. Use lower temperature when the answer should stay close to the source. Use higher temperature only when variation is part of the task and some drift is acceptable.
Practical temperature selection
Choose temperature based on task class:
- Low for factual extraction, policy summaries, and compliance-sensitive outputs.
- Medium for balanced drafting where mild variation is useful.
- High for ideation tasks where novelty is preferred over strict fidelity.
One global setting rarely works across all workflows.
Common mistakes
- Using high temperature for fact-critical tasks.
- Blaming model quality when randomness setting is the real issue.
- Not controlling seed or run comparisons during evaluation.
- Ignoring interaction with other decoding parameters.
Quality checks
- Does output stay faithful to source facts at chosen setting?
- Are runs stable enough for production reliability?
- Is creativity level appropriate for task risk?
- Are parameter choices documented for repeatability?
Temperature is a control for variance. Use it deliberately, not by default, and align it with reference sources fidelity needs.
Implementation discussion: Ajey (prompt operations lead), the QA analyst, and the content strategist define temperature bands by task class (policy, summary, ideation), run controlled comparisons on fixed prompt sets, and lock default settings for high-risk factual workflows. They measure success through stable factual fidelity with predictable output variance.
