Why would you expect this to be identical in the first place? There are too many factors here that are not accounted for (and using a model INSIDE a PL model seems very bad practice to begin with).

Your code might not be deterministic. Even for a single model, this will lead to different results in two separate runs.
Read the PyTorch documentation on Reproducibility 2 and torch.use_deterministic_algorithms 1

Even when deterministic, the models won’t necessarily be identical
Different model implementation will not necessarily have the exact loss per-step, but should converge in a similar manner
Even if the models were identical, and you fixed the initial random seed, the outputs would STILL be different because you are training two models at the same time. That means that the seeds that are used at every step are NEVER THE SAME (or highly unlikely). So first you init model 1 and then model 2, but those will be initialised differently because the next RNG number is called for the seed.

In sum: you should not expect that two models (different or not) output the exact same loss when run consecutively in the same script.
Also, for the future: please have more patience and do not tag people so urgently. 24h have not even passed since you posted this question. We are all willing to help, but if every new question was tagging us, it would be very tiresome.