Compare temperature and top-p settings to see how they affect randomness and control.
A sampling settings guide with live sliders. See how temperature and top-p change determinism, diversity, and best-use cases. Great for developers tuning assistants, marketers writing prompts, and teams trying to understand model output behavior.
Got questions? We’ve got answers. Here are some of the most common inquiries about Temperature & Top-P Explainer.
Temperature & Top-P explainer
What it means
Temperature 0.70 controls randomness. Top-p 0.90 truncates the token pool to the most likely candidates.
Best for: General chat, support, summaries
Rule of thumb
Lower temperature = fewer surprises. Lower top-p = smaller candidate pool. Use both together when you need predictable output.
Tip
Temperature and top-p both shape randomness. In production, usually change one at a time so you can see what actually moved the output.