Why does np.linalg.solve give me an error when trying to solve a 16x16 system of equations?

I'm creating an nxn matrix with the largest value being n**n. np.linalg.solve works when n < 16, but for n >= 16, it gives an error:

numpy.core._exceptions.UFuncTypeError: Cannot cast ufunc 'solve1' input 0 from dtype('O') to dtype('float64') with casting rule 'same_kind'

Here's my code:

import numpy as np

def fib_to(n):
    if n==0: return [0]
    fibs = [0, 1]
    for i in range(2, n+1):
        fibs.append(fibs[-1] + fibs[-2])
    return fibs

def get_nth_matrix(n):
    coeficients = [[i**j for j in range(n, -1, -1)] for i in range(n+1)]
    augment = fib_to(n)
    return coeficients, augment

print(np.linalg.solve(*get_nth_matrix(16)))

I also noticed that doing np.linalg.cond on the matrix had the same problem. It worked for values up to 15, but gave a division by 0 error when n was 16 or greater