For developers and learners tuning model settings who want to know what the numbers actually do. You get a plain explanation for any temperature from 0 to 2 and top-p from 0 to 1.
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You enter
Temperature 0.2, top-p 0.9
The tool shows
Temperature 0.2: low, focused and repeatable, good for factual answers and structured output. Top-p 0.90: trims only the long tail of unlikely tokens
Use 0 or close to it, so the model picks the most likely token each time and results are repeatable. The explainer calls 0 greedy or deterministic.
Temperature reshapes the whole probability distribution, while top-p keeps only the smallest set of tokens whose probabilities add up to p and samples from those.
Usually change only one. Adjusting both makes it hard to tell which caused a change in output.
Yes. It is free, needs no sign-up and runs entirely in your browser, so what you type is not uploaded. You only sign in if you want to email a result to yourself or save it to your CareerByteCode profile.
