Are you saying that given a fixed data and a fixed model, you get different outputs on every different forward pass?
To answer the dropout part, yes model.eval() is necessary to turn off dropout during inference.
Can you see if the model is loaded in the first place and that there are no random initialization of params during every forward pass?