Memory usage of `numpy.random`

Consider the following script:

import numpy as np
import tracemalloc

def zero_mem():
    a = np.zeros((100, 100))

def nonzero_mem():
    b = np.random.randn(100, 100)


if __name__ == "__main__":
    tracemalloc.start()
    zero_mem()
    print(tracemalloc.get_traced_memory())
    tracemalloc.stop()

    tracemalloc.start()
    nonzero_mem()
    print(tracemalloc.get_traced_memory())
    tracemalloc.stop()

The output running numpy 1.22.2 on python 3.8.10 is

(0, 80096)
(72, 80168)

The question is: why isn't the second row (0, 80168)? In other words: why is there memory still in use after nonzero_mem(), unlike when calling zero_mem()?