Why is heap slower than sort for K Closest Points to Origin?

The coding task is here

The heap solution:

import heapq
class Solution:
    def kClosest(self, points: List[List[int]], K: int) -> List[List[int]]:
        return heapq.nsmallest(K, points, key = lambda P: P[0]**2 + P[1]**2)

The sort solution:

class Solution(object):
    def kClosest(self, points: List[List[int]], K: int) -> List[List[int]]:
        points.sort(key = lambda P: P[0]**2 + P[1]**2)
        return points[:K]

According to the explanation here, Python's heapq.nsmallest is O(n log(t)), and Python List.sort() is O(n log(n)). However, my submission results show that sort is faster than heapq. How did this happen? Theoretically, it's the contrary, isn't it?

from Why is heap slower than sort for K Closest Points to Origin?