# Do AI models recommend the same brands? | Trakkr Research

Canonical URL: https://trakkr.ai/trakkr-research/model-divergence/answers/do-ai-models-recommend-the-same-brands
Published: 2026-03-11
Last updated: 2026-03-11
Author: Mack Grenfell

Not usually. Average agreement across the study is only 43.3%, and only 4.0% of prompts produced perfect agreement across all models tested.

## 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

Rarely. Average agreement across the study is only 43.3 percent, and only 4.0 percent of prompts produced perfect agreement across all 8 models tested.

## What this means

Operators cannot rely on a single AI platform as a proxy for overall market visibility. Resource allocation must account for platform divergence to accurately measure and influence brand presence.

## 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

### How often do all AI models agree on brand recommendations?

Perfect agreement across all 8 models analyzed occurs in only 4.0 percent of prompts.

### What is the average rate of agreement between different AI platforms?

The mean cross-model agreement rate is 43.3 percent.

### Which models were included in this analysis?

The study analyzed 8 models including OpenAI, Anthropic, Gemini, Grok, Deepseek, Meta, Perplexity, and Google AI Overviews.

## What to do next

- [Track visibility across multiple models instead of using one platform as a proxy for the whole market.](https://trakkr.ai/trakkr-research/model-divergence/answers/do-ai-models-recommend-the-same-brands#next-step-1)
- [Prioritize query classes where disagreement is highest because that is where share can move fastest.](https://trakkr.ai/trakkr-research/model-divergence/answers/do-ai-models-recommend-the-same-brands#next-step-2)
- [Treat consensus as a benchmark but treat divergence as the operating reality.](https://trakkr.ai/trakkr-research/model-divergence/answers/do-ai-models-recommend-the-same-brands#next-step-3)

## Related pages

Continue through the same study cluster.

- [how often is there perfect consensus across models](https://trakkr.ai/trakkr-research/model-divergence/answers/how-often-is-there-perfect-consensus-across-models) - Related answer page
- [how much do models disagree on brand recommendations](https://trakkr.ai/trakkr-research/model-divergence/answers/how-much-do-models-disagree-on-brand-recommendations) - Related answer page
- [average cross model agreement is only forty three percent](https://trakkr.ai/trakkr-research/model-divergence/facts/average-cross-model-agreement-is-only-forty-three-percent) - Related fact page
- [query class agreement tracker](https://trakkr.ai/trakkr-research/model-divergence/trackers/query-class-agreement-tracker) - Related tracker page

## Data And Sources

- [Same Question, Different AI, Different Answers](https://trakkr.ai/trakkr-research/model-divergence) - Flagship study behind this page
- [Page JSON](https://trakkr.ai/data/research-answers/model-divergence/answers/do-ai-models-recommend-the-same-brands.json) - Machine-readable companion file