Comparing Dataset - Should I use the same Test dataset?
By testing a model on the same dataset (sharing same characteristics), you will have information on how pertinent you hyperparameters are for this dataset.
Then you can test on another dataset that has other characteristics. It will give you information on how good is a model to generalize.
I would not create a mixed dataset to test the model for interpretation as it could hide some interesting information. For instance, case 1 you predict 100% of the samples from test dataset A and only 50% from test dataset B. Case 2 you predict 75% from both. Interpretation will not be the same. But If you want to compare the two models created from 2 different training datasets, then yes, compare them with a same test dataset, otherwise the test would be biased.