Top-p Sampling
Definition
Top-p sampling adapts the selection of next text tokens to their probabilities.
A decoding method that forms the smallest token set with cumulative probability at least p and samples from it.
Simply explained
The AI collects the most probable text pieces until their combined probability reaches the set threshold. It then draws the next piece from this selection.
Why it matters in practice
The term helps to select, develop, evaluate AI systems in a well-founded manner and realistically assess their technical risks.
Example from business
A product text generator evaluates p values with fixed quality and compliance checks.
Limits and pitfalls
- Top-p guarantees neither truth nor creativity; temperature, minimum tokens, and implementation details change the result.
Origin & history
Holtzman and coauthors published Nucleus Sampling in 2019 as a dynamic alternative to fixed Top-k.
Use in mid-sized companies
- Possible application: A product text generator evaluates p-values with fixed quality and compliance checks.
Frequently asked questions
What does Top-p Sampling mean?
A decoding method that forms the smallest set of tokens with a cumulative probability of at least p and samples from it. What should be considered? Top-p does not guarantee truthfulness or creativity; temperature, minimum tokens, and implementation details affect the result.
Sources
- The Curious Case of Neural Text Degeneration · Holtzman et al., The Curious Case of Neural Text Degeneration
Source checked on 10.10.2026. Editorial application examples are hypothetical; no evidence of real customer results.
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