I measured Go 1.27's experimental simd package against NumPy. They tie out of cache and lose inside it, and the reason is not the language.
Go 1.27 shipped a simd package in the standard library. It is experimental and sits behind a flag, and every write-up I found described the API. None of them said when it actually helps.
So I measured it against NumPy on the same task: a speaker-search index, 346 thousand vectors of 192 dimensions, 66 million multiplications per query.
The answer turned out not to be about Go or NumPy at all.
Same code, two verdicts
With a 253 MB corpus, single-threaded:
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