Temperature (AI), explained
Temperature is a setting that controls how predictable or varied an AI model's responses are — low values produce focused, consistent output; high values produce more creative, unpredictable output.
When an AI model generates text, it's constantly choosing the next word from a ranked list of possibilities. Temperature is the dial that decides how strictly it sticks to the top choice. At a low temperature (close to 0), the model almost always picks the most likely word, so responses are consistent and on-point. At a high temperature (closer to 1 or beyond), the model sometimes picks lower-ranked words, which produces more variety — and occasionally more surprise.
In practice, this means a low temperature is useful when accuracy matters: writing SQL, extracting specific facts, filling out forms. A high temperature suits tasks where variety is the point: brainstorming names, generating ad copy variations, or exploring creative directions. Most AI tools expose this as a slider or a numeric field in settings.
Temperature doesn't change what the model knows — it changes how adventurous it is when constructing an answer. A model set to 0 on a trivia question will give you the same answer every time. The same model set to 0.9 might occasionally rephrase, tangent, or invent. That's not a bug; it's the tradeoff you're choosing.
Go deeper
Wield's Prompting track covers this hands-on, in plain English, with real examples and a copy-paste prompt to try it yourself.
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