Hi @pstenge2 ,
So far I know the principle for a simple model target recognition should be the same.
The model , Image Targets and the Vumarks in Vuforia should work for the stability aspect similar comparing to Vuforia Engine. There could be also difference based on your device or the used tool (e.g. Untiy or Android Studio etc.) But the best way will be to test it your own model target to test the difference. Because I do not think that this could be answered generally. Maybe for Studio if your model is to complex you can use a second simplified model for the creation of the model target in studio project where the object recognition is working better.
In Vuforia engine currently there are more features for targeting
https://library.vuforia.com/content/vuforia-library/en/features/overview.html
So, in Vuforia Engine you have e.g. the advanced Model target Database which could enable your app to detect an object from a full 360-degree view around the physical object.
https://library.vuforia.com/content/vuforia-library/en/articles/Solution/trained-model-target-datasets.html
I did in the past some tests also in Vuforia Engine on Unity with small test projects but could not find some significant differences for the recognition stability to studio… but … may be somebody could share here another experience…
Another aspect is for example if you come from the Creo World – then it is more difficult to import models to e.g. Unity , for example sequences and figures generated in Creo Illustrate , but for e.g. AutoDesk models there is a good support options in Unity
Other point is that for the same functionality is the complexity of the programming in Unity higher comparing to the achieving of the same functionality in Studio
