Best-of prompts carry a high-divergence tail | Trakkr Research
The study Same Question, Different AI, Different Answers evaluated model consistency and found that best-of prompts frequently split models.
Methodology: Built from 797,644 valid comparisons across 44,088 reports and 8 models, covering 6,439,133 model responses in the observed window.
Claim
Best-of prompts show a 14.8 percent high-divergence rate in the model divergence study.
Why it matters
Strategists should treat best-of content as a high-risk visibility category that requires diversified optimization tactics to account for inconsistent model outputs.
Supporting metrics
| Metric | Value | Context |
|---|---|---|
| Best-of high divergence | 14.8% | Best-of prompts frequently split models. |
Related pages
Continue through the same study cluster.
- should you use one model as a proxy for all ai visibility - Related answer page
- why do models disagree so much even on common categories - Related answer page
- query class agreement tracker - Related tracker page
Data & Sources
- Same Question, Different AI, Different Answers - Flagship study behind this page
- Page JSON - Machine-readable companion file