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IMO this is just not a great example on either side. As others have pointed out, the Julia implementation was refined to be 8x faster. The Mojo code has to run the CPython interpreter to run numpy.

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The example Mojo code does not run the computations with numpy. It uses the extensions of Mojo to do it, testing the capabilities of this extensions, which are the ones who promises the speed up. I must admit otherwise that not a lot of work has been done to optimise it as the optimised Julia version.

Why are you saying that? The Mojo code seems to have the same optimizations as the Julia code.

Edit: I see your point now. Still, I don't know if there is some specific idiom that the current version of the compiler may optimise better. :)

> The Mojo code has to run the CPython interpreter to run numpy.

Yes, the need to run CPython interpreter is what makes Mojo slow (and it will remain that way, unless they abandon their "superset of Python" promise).

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