Glossary
Best-of-N
In short
Generating several candidate answers and keeping the best one, instead of trusting a single attempt.
A model’s first attempt is not always its best. Best-of-N generates several candidates, from one model or many, then selects or fuses the strongest. More attempts give you a better ceiling to pick from.
It trades a bit more cost for noticeably better quality, which is worth it when the answer matters more than speed.
In LLMWeave
A best-of-N weave produces several candidate answers and then picks or fuses the best, so your final result is the strongest of the bunch rather than a single roll of the dice.
Related terms
LLM as a judge
Using one model to evaluate, rank, or merge the outputs of other models.
Model ensemble
Combining the outputs of several models into one result, so the group performs better than any single member.
Multi-model AI
Using more than one AI model on the same task, instead of relying on a single model for every answer.
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