Should you use one model as a proxy for all AI visibility? | Trakkr Research
No. With only 43.3% average agreement and 4.0% perfect consensus, one model is an unreliable proxy for the wider AI market.
Methodology: Built from 797,644 valid comparisons across 44,088 reports and 8 models, covering 6,439,133 model responses in the observed window.
Direct Answer
No. With only 43.3% average agreement and 4.0% perfect consensus across 8 models, one model is an unreliable proxy for the wider AI market.
What this means
Relying on a single model for visibility metrics leads to blind spots in resource allocation. Teams must use multi-model tracking to accurately decide which content to publish, refresh, or measure next.
Evidence table
| Metric | Value | Why it matters |
|---|---|---|
| Average agreement | 43.3% | Mean cross-model agreement rate. |
| Perfect agreement | 4.0% | Only a small share of prompts produce unanimous outcomes. |
| Models analyzed | 8 | OpenAI, Anthropic, Gemini, Grok, Deepseek, Meta, Perplexity, and Google AI Overviews. |
Frequently Asked Questions
Which models were included in the 8 platforms analyzed?
The analysis included OpenAI, Anthropic, Gemini, Grok, Deepseek, Meta, Perplexity, and Google AI Overviews.
What does the 4.0% perfect agreement metric mean for my tracking strategy?
It indicates that only a small share of prompts produce unanimous outcomes across all 8 models, meaning you cannot assume a top rank in one model guarantees visibility in the others.
What to do next
Related pages
Continue through the same study cluster.
- why do models disagree so much even on common categories - Related answer page
- what is the operational cost of model divergence - Related answer page
- best of prompts carry a high divergence tail - Related fact 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