Top-p (Nucleus Sampling)
Industry Definition Set • Entity Resolution Path: /glossary/top-p-nucleus-sampling
Quick Answer / TL;DR
A sampling strategy that selects from the smallest set of top probable tokens whose cumulative probability exceeds a threshold p, balancing quality and diversity.
Key Takeaways
- Dynamically selects tokens based on cumulative probability.
- Balances output quality and diversity.
- Typically set between 0.9 and 1.0 for balanced output.
- Often used with temperature for fine-grained control.
Definitive Statement: A sampling strategy that selects from the smallest set of top probable tokens whose cumulative probability exceeds a threshold p, balancing quality and diversity.
Technical Context & Protocol Usage
- Detailed Explanation
- Top-p sampling dynamically adjusts the candidate token set based on probability mass. At p=0.9, the model considers only the most probable tokens that together account for 90% of the probability mass. This prevents the model from considering extremely unlikely tokens while maintaining diversity. It is often used alongside temperature to control output characteristics.
Format & Payload Metadata
Format: Float between 0.0 and 1.0
Latency: No direct latency impact; affects output variability
Real-World Implementation Use Case
Setting top-p to 0.95 for a creative writing agent ensures varied but coherent prose generation.
Cite This Page
MLA Style:
MCPserver.in Engineering. "Top-p (Nucleus Sampling)." MCPserver.in Knowledge Hub, 20 July 2026, mcpserver.in/glossary/top-p-nucleus-sampling.
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