Why is numpy.array so slow?

I am baffled by this

def main():
    for i in xrange(2560000):
        a = [0.0, 0.0, 0.0]

main()

$ time python test.py

real     0m0.793s

Let's now see with numpy:

import numpy

def main():
    for i in xrange(2560000):
        a = numpy.array([0.0, 0.0, 0.0])

main()

$ time python test.py

real    0m39.338s

Holy CPU cycles batman!

Using numpy.zeros(3) improves, but still not enough IMHO

$ time python test.py

real    0m5.610s
user    0m5.449s
sys 0m0.070s

numpy.version.version = '1.5.1'

If you are wondering if the list creation is skipped for optimization in the first example, it is not:

  5          19 LOAD_CONST               2 (0.0)
             22 LOAD_CONST               2 (0.0)
             25 LOAD_CONST               2 (0.0)
             28 BUILD_LIST               3
             31 STORE_FAST               1 (a)