Temperature

You might say

Why does AI phrase the answer differently when I ask the same question again?

A parameter that adjusts sampling randomness in generation APIs and models that support itWhen asking AI to name a to-do app, a higher temperature usually allows more varied wording; for a response with a fixed format, a lower setting may reduce variation. It cannot lock outputs to identical wording, and support and ranges differ by model and API.

Know first

Prompt

Temperature

How can temperature change answers to the same request?

Generation settings · example

Write a slogan for a to-do appLower-temperature trend

Option AMake today’s tasks easier to organize.

Option BOrganize today’s to-dos more clearly.

ObservationSimilar idea; wording still varies

Teaching example, not a measurement: lower temperature often concentrates candidates, but does not make every word identical.

Temperature affects sampling, not format checks

First check API support: For models and APIs that support it, lower values usually concentrate sampling and higher values usually add variation. Check the relevant documentation for supported ranges.

Constrain a required format separately: A low setting can still produce missing or incorrect fields. Define the structure and validate the actual output.

You can say this to an AI Agent

First check whether this model and API support temperature. Compare candidates for the same naming request at different settings, treating them as a trend in randomness rather than a guarantee that low temperature repeats every word. If the format must be fixed, define it separately and validate the result.

What to learn next

1Structured Output→2Prompt→

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The team asks AI to name a to-do app, but the suggestions sound alike. If the API supports temperature, what should you try first?

A. Lower the temperature so the candidate names differ moreB. Increase the maximum output length to give the model more wordsC. Raise the temperature somewhat, then compare another set of names