I think a performance difference with these two implementations is expected, as converting to tensors before stacking introduces a second iteration step in Python (which will be slower than doing everything in a single native function like numpy.stack). However, I can’t reproduce the 10x difference (it might be because my environment or timing) is somewhat different.
If you have a small code snippet that shows the 10x difference it might be easier to see if there is another issue, but as is I would expect converting to tensors after stacking in numpy to be faster.