generally numpy closes the gap to within 2x as long as all your operations are easily vectorizable, and none of your arrays have a size less than 100 or so. for

generally numpy closes the gap to within 2x as long as all your operations are easily vectorizable, and none of your arrays have a size less than 100 or so. for small arrays, numpy is around 1000x slower than Julia because every operation has a large overhead (somewhere in the range of 10 us)