Temperature & Top-K Explainer
Adjust the sliders to understand how temperature, top-k, and top-p affect model behavior. Lower values = more predictable. Higher values = more creative.
Balanced (default)
Moderate diversity
Adaptive diversity
Plain English Explanation
What These Parameters Do
Temperature
Controls randomness of token selection:
- 0.0: Deterministic (always picks highest probability token)
- 0.5-1.0: Balanced and natural
- 1.5+: Creative but may be incoherent
Top-K
Only sample from the top K most likely tokens:
- Low (1-10): Very focused, predictable
- Medium (20-50): Balanced diversity
- High (100+): More variety, less focused
Top-P (Nucleus Sampling)
Sample from smallest set of tokens with cumulative probability ≥ P:
- 0.5: Conservative, very predictable
- 0.9: Good balance (recommended)
- 1.0: No filtering, all tokens considered
Related Tools
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- Prompt Template Generator – Create structured prompts