What Is Temperature in AI Models?
In AI language models, temperature is a setting that controls how random the output is. A low temperature makes the model pick the most likely next tokens, producing more predictable and focused text; a higher temperature allows less likely choices, producing more varied and creative, but less consistent, output.
Choosing a Temperature
Lower values are often used for factual answers, extraction, and code; higher values for brainstorming and creative writing. The exact scale depends on the model provider.
Randomness and Sampling
Temperature changes the probabilities used when the model samples its next token, similar to adjusting how evenly weighted a random draw is.
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Last updated: September 29, 2026. This definition is for general educational purposes only. It is not financial, investment, tax, legal, or medical advice, and it does not recommend any product or course of action. For decisions about your own situation, consult a qualified professional.