Based on the source code of MxNet:
factor = (fan_in + fan_out) / 2.0
...
scale = np.sqrt(self.magnitude / factor)

Their docs show the function:
c = \\sqrt{\\frac{3.}{0.5 * (n_{in} + n_{out})}}
Which could possibly mean that the default magnitude=3 is the one in frac{3}
So they have in the upper part of the fraction (inside sqrt) 3(magnitude) * 2(the 0.5 in the denominator)
In PyTorch gain acts differently.
If we take it inside the function we will have gain^2 * 6 which should be equal to the MxNet magnitude*2 which makes gain = sqrt(magnitude/3) meaning that our magnitude of 0.0003 would be a gain of sqrt(0.0003/3) = 0.01
Which is still weird given that I am getting different ranges of results.
It may be a question more suitable for the MxNet forum so I will ask it there, make sure to reach a solution, then go back here to post either a link to the solution or my own explanation of it.
Thank you @ptrblck for taking the time to check it out!