There sure is 
outp1 = model1(inputs) # is of shape (batch_size, 100)
outp2 = model2(inputs)

indexes = torch.tensor([0,1,2,3])

spec1 = outp1.index_select(dim=1, index=indexes) # Selects nodes at indexes over the whole batch
spec2 = outp2.index_select(dim=1, index=indexes)

Here is isolated code that you can run to experiment.
import torch

outp1 = torch.randn(2, 5)
outp2 = torch.randn(2, 5)
indexes = torch.tensor([0,1,2])

spec1 = outp1.index_select(dim=1, index=indexes)
spec2 = outp2.index_select(dim=1, index=indexes)


print("Output1: \n%s\n" % outp1)
print("Output2: \n%s\n" % outp2)
print("Selected1: \n%s\n" % spec1)
print("Selected2: \n%s\n" % spec2)