Free temperature & top-p explainer — visualize how sampling parameters change LLM creativity and consistency.
Was Temperature & Top-P Explainer useful?
Your vote helps us prioritize improvements.
The QuickToolz Temperature & Top-P Explainer demystifies LLM sampling parameters. Slide the temperature and top-p controls and see — on a real token-probability chart — how outputs change from deterministic to wildly creative.
Temperature (0–2): scales the logits. 0 = deterministic argmax. 1 = neutral. >1 flattens the distribution (more random).
Top-p (nucleus sampling): keeps only the smallest set of tokens whose cumulative probability ≥ p. Smaller p = safer choices.
Top-k: keeps only the top-k tokens. Less common in modern APIs.
Use temperature for "how wild" and top-p for "how risky". Most production deployments use temperature 0.0–0.7 and top-p 0.9–1.0.
Everything you need, nothing you don’t. Built for speed and simplicity.
Token probability chart updates as you slide.
What each setting will actually do to output.
Deterministic, balanced, creative, brainstorm — one-click presets.
Everything you need, nothing you don’t. Built for speed and simplicity.
Slide from 0 (deterministic) to 2 (chaotic).
Got questions? We’ve got answers. Common questions about Temperature & Top-P Explainer.
Slide from 0 (greedy) to 1 (full vocabulary).
See live token probabilities under each setting.
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.