Top-K Sampling Playground
Simulate Top-K truncation filtering. Adjust K to prune unlikely tokens and view re-normalized probability distributions.
Concept Breakdown: How Language Models Sample & Select Tokens
At Temperature 0.1, you always pick vanilla. It is safe and predictable. At Temperature 1.5, you randomly pick chili-mango or bubblegum. High temperature makes AI creative; low temperature makes it factual.
Top-K says: "Only consider the top K contenders". If K=3, the AI throws away all other candidates and only chooses between the 3 frontrunners, preventing weird typos or nonsense words.
Top-P (Nucleus) adds probabilities until reaching P (e.g. 90%). If the model is 95% certain about one word, it picks that word immediately. If uncertain, it widens the net to include several good alternatives.
Quick Reference & Instructions
Simple steps, pro tips, and execution details
Provide Inputs
Type, paste, or select your values in the form fields below.
Instant Live Analysis
Calculations and formatting happen automatically with zero delay as you type.
Copy or Use Output
Copy results or apply the clean output directly to your projects.
How It Works
Orders candidates by probability descending, keeps strictly the top K choices, and scales their sum to 100%.
Frequently Asked Questions
Common questions about calculations, assumptions, and edge cases.
Yes, Top-K Sampling Playground is 100% free with unlimited calculations and zero paywalls or subscriptions.
Related Tools
Explore all llm tools →Top-P (Nucleus) Sampling Playground
Interactive nucleus sampling. Set cumulative probability threshold P (e.g. 0.90) to see dynamic candidate set selection.
LLM Temperature Playground
See how the Temperature hyperparameter flattens or sharpens the sampling probability distribution in real-time.
LLM Generation Simulator
Watch an LLM generate text step by step: Tokenize → Forward Pass → Softmax → Sampling → Append → Repeat.