Cython: why is size_t faster than int?

Changing certain Cython variables from type int to type size_t can significantly reduce some functions speeds (~30%), but I do not understand why.

For example:

cimport numpy as cnp
import numpy as np

def sum_int(cnp.int64_t[::1] A):
    cdef unsigned long s = 0
    cdef int k
    for k in xrange(A.shape[0]):
        s += A[k]
    return s

def sum_size_t(cnp.int64_t[::1] A):
    cdef unsigned long s = 0
    cdef size_t k
    for k in xrange(A.shape[0]):
        s += A[k]
    return s

a = np.array(range(1000000))

And the timing results:

In [17]: %timeit sum_int(a)   
1000 loops, best of 3: 652 µs per loop

In [18]: %timeit sum_size_t(a)
1000 loops, best of 3: 427 µs per loop

I am new to Cython, and know Fortran better than C. Help me out. What is the important difference between these two variable types that causes such a performance difference? What is it that I don't grok about Cython?