What Is Temperature in AI Models?
Temperature is a parameter that controls the randomness of AI text generation. Lower values (e.g., 0.0) produce more deterministic, predictable outputs. Higher values (e.g., 1.0) produce more diverse, creative outputs.
Frequently Asked Questions
When should I use temperature 0?
For tasks requiring consistency: extraction (data from documents), classification, factual answers, code generation, structured outputs. Lower temperature reduces variance — same input produces nearly the same output.
When should I use higher temperature?
For creative tasks: brainstorming, generating alternatives, fiction writing, breaking out of repetitive patterns. Temperature 0.7-1.0 produces more variety. Temperature above 1.0 can produce incoherent output.
What is the default temperature?
Most APIs default to 1.0. Most chat interfaces (ChatGPT, Claude.ai) use values around 0.7 internally. For programmatic use, set explicitly based on task needs.
Does temperature affect quality?
Indirectly. Lower temperature is "safer" — the model picks high-probability tokens. Higher temperature is more creative but can degenerate. For most professional tasks, temperatures between 0.0 and 0.7 produce best results depending on use case.
What is top-p?
Top-p (nucleus sampling) is an alternative randomness parameter that selects from the smallest set of tokens whose cumulative probability exceeds a threshold. Top-p 0.9 means "consider tokens that together make up 90% of probability mass." Often used alongside temperature.
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