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llms.txt GeneratorAverage cross-model agreement is only 43.3%
Average cross-model agreement in the model divergence study is 43.3 percent across 797,644 valid comparisons.
Agreement is meaningfully below the level most teams assume.
The numbers behind it.
- Average agreement
- Mean cross-model agreement rate.
- 43.3%
- Valid comparisons
- Cross-model recommendation comparisons in the study.
- 797,644
The evidence.
| Measure | Result |
|---|---|
| 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
Strategists and operators must treat each artificial intelligence model as a distinct visibility surface, as the low agreement rate indicates that optimizing for one model does not guarantee visibility or consistent answers across others.
Cite this fact.
Source study: Model Divergence“Average cross-model agreement in the model divergence study is 43.3%.”
Same Question, Different AI, Different Answers - Trakkr Research · Average cross-model agreement is only 43.3%
Same Question, Different AI, Different Answers · Trakkr Research · Updated 11 March 2026