Not sure where to start? Take a guided tour.
AI Site Grader
AI Query Scanner
llms.txt GeneratorHow much do models disagree on brand recommendations?
A lot. 14.6% of prompts fall into the high-divergence bucket, and average agreement is still only 43.3% even when measured across a large, cleaned comparison set.
The key numbers.
- High divergence rate
- Prompts in the 0-25% agreement bucket.
- 14.6%
- Average agreement
- Mean cross-model agreement rate.
- 43.3%
- Valid comparisons
- Cross-model recommendation comparisons in the study.
- 797,644
This is enough disagreement to treat each model as its own acquisition channel.
The evidence.
| Measure | Result |
|---|---|
| High divergence rate Prompts in the 0-25% agreement bucket. | 14.6% |
| Average agreement Mean cross-model agreement rate. | 43.3% |
| Valid comparisons Cross-model recommendation comparisons in the study. | 797,644 |
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 answer matters because it turns a study finding into an operating rule teams can use when they decide what to publish, refresh, or measure next.
Questions about this answer.
Cite this answer.
Source study: Model Divergence“A lot. 14.6% of prompts fall into the high-divergence bucket, and average agreement is still only 43.3% even when measured across a large, cleaned comparison set.”
Mack Grenfell · How much do models disagree on brand recommendations?
Same Question, Different AI, Different Answers · Trakkr Research · Updated 11 March 2026