Not sure where to start? Take a guided tour.
AI Site Grader
AI Query Scanner
llms.txt GeneratorWhat should brands do when models disagree?
Mostly, brands should treat divergence as the default condition. That means tracking multiple models, watching query classes separately, and using cross-model data to find where visibility is actually portable.
The key numbers.
- Average agreement
- Mean cross-model agreement rate.
- 43.3%
- Best-of high divergence
- Best-of prompts frequently split models.
- 14.8%
- Comparison-query agreement
- Comparison prompts produce the highest average agreement.
- 50.4%
The goal is not perfect consensus. It is resilient coverage across the models that matter, ensuring strategies account for varying AI responses rather than relying on a single source of truth.
The evidence.
| Measure | Result |
|---|---|
| Average agreement Mean cross-model agreement rate. | 43.3% |
| Best-of high divergence Best-of prompts frequently split models. | 14.8% |
| Comparison-query agreement Comparison prompts produce the highest average agreement. | 50.4% |
Population and method
Built from 797,644 valid comparisons across 44,088 reports and 8 models, covering 6,439,133 model responses in the observed window.
Where the evidence stops
Agreement is measured across recommendation outputs, not across hidden reasoning or retrieval context.
Average agreement can hide large differences between query classes and model pairs.
The study measures overlap, not which answer was objectively “right”.
What to do with this
- Track visibility across multiple models instead of using one platform as a proxy for the whole market.
- Prioritize query classes where disagreement is highest because that is where share can move fastest.
- Treat consensus as a benchmark, but treat divergence as the operating reality.
This turns a study finding into an operating rule teams can use when they decide what to publish, refresh, or measure next, preventing over-reliance on a single model proxy.
Questions about this answer.
Cite this answer.
Source study: Model Divergence“Mostly, brands should treat divergence as the default condition. That means tracking multiple models, watching query classes separately, and using cross-model data to find where visibility is actually portable.”
Mack Grenfell · What should brands do when models disagree?
Same Question, Different AI, Different Answers · Trakkr Research · Updated 11 March 2026