# Best-of-N Sampling

> Best-of-N sampling generates N candidate outputs and returns the one ranked highest by a verifier, reward model, or scoring function.

- Identifier: PTL-0054
- Category: Self-Critique & Verification
- Canonical URL: https://protologue.com/t/best-of-n-sampling/
- Also known as: rejection sampling, best-of-n, BoN

## Description

It is the simplest form of trading inference compute for quality. Its effectiveness depends on the verifier, and optimizing too hard against an imperfect reward model can select outputs that game it.

## Related terms

- [Self-Consistency](https://protologue.com/t/self-consistency/)
- [Process Reward Model](https://protologue.com/t/process-reward-model/)
- [Test-Time Compute Scaling](https://protologue.com/t/test-time-compute-scaling/)

## Sources

- Lightman et al. (2023). Let's Verify Step by Step. https://arxiv.org/abs/2305.20050
- Snell et al. (2024). Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters. https://arxiv.org/abs/2408.03314

## Cite this entry

Protologue. (2026). Best-of-N Sampling. In Protologue: A Taxonomy of Prompting and LLM Techniques (v1.0.0, PTL-0054). https://protologue.com/t/best-of-n-sampling/

License: CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/)