Artificial Intelligence
Temperature
A parameter that controls the randomness or creativity of an LLM's output. Lower temperatures (closer to 0) make outputs more deterministic and focused; higher temperatures increase randomness and creativity.
Why It Matters
Temperature control lets you tune the same model for different use cases — precise factual answers at low temperature, creative brainstorming at high temperature.
Example
At temperature 0, asking 'Name a color' always returns 'Blue.' At temperature 1.0, it might return 'Cerulean,' 'Magenta,' or 'Chartreuse' — more varied and surprising.
Think of it like...
Like a spice dial in cooking — turn it low for a consistent, predictable dish, or crank it up for bold, unexpected flavor combinations.