Why are my results different from one AI model to another?
Seeing strong visibility on ChatGPT but little on Gemini? That's normal and useful — not a bug.
Each model is different. ChatGPT, Perplexity, and Gemini pull from different sources, were trained differently, and each has its own "personality." So the same question can surface different brands depending on which engine answers it.
Why GetMint tracks all three: measuring across engines shows you where you're already winning and where you're invisible. Being strong on one and absent on another tells you exactly where to focus your effort next.
How to read it:
- Compare your visibility per engine for the same topic.
- For the engine where you're weak, check which sources it cites — they're often different from the engine where you're strong.
- Build presence in those specific sources to close the gap on that engine.
One more factor: models are non-deterministic, so even a single engine won't give identical answers every time. GetMint accounts for this by running repeated simulations and reporting a probability. Read the trend, not one snapshot.
Don't expect the engines to agree — use the differences as a map of where to work.
Key takeaways
- Cross-model variance is normal, not a bug — different sources, different training, different personality per engine.
- Compare visibility per engine for the same topic to find where you're already winning and where you're invisible.
- The engine where you're weak has its own cited-source mix — build presence there to close the gap.
- Models are non-deterministic — read the trend, not one snapshot.