Cupy was outputting the floats as a cupy.array in the tuple comprehension above whereas numpy outputted the floats as floats. Changing the code to this produced the desired output:

import cupy as cp

def sortBis(mat: np.ndarray): 
    colInds = cp.lexsort(mat[:, 1:]) mat[:, 1:] = mat[:, 1:][:, colInds] 
    return mat

newMat = cp.array([[ 0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  1.], [ 0.,  1.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0., -1.]]

newMatSet.add(tuple(tuple(float(i) for i in row) for row in sortBis(newMat)))