Interesting, but misguided, I think.

If you've selected Python as your programming language, then your problem is likely either to do some text processing, a server-side lambda, or to provide a quick user interface. If you're using it for eg. Numpy, then you're really using Python to load and format some data before handing it to a dedicated maths library for evaluation.

If you've selected Go as your programming language, then your problem is likely to be either networking related - perhaps to provide a microservice that mediates between network and database - or orchestration of some kind. Kubernetes is the famous one, but a lot of system configuration tools use it to manipulate a variety of other services.

What these uses have in common is that they're usually disk- or network- limited and spend most of their time waiting, so it doesn't matter so much if they're not super efficient. If you are planning to peg the CPU at 100% for hours on end, you wouldn't choose them - you'd reach for C / C++ / Rust. Although Swift does remarkably well, too.

Seeing how quickly you can solve Fannkuch-Redux using Python is a bit like seeing how quickly you can drive nails into a wall using a screwdriver. Interesting in its way, but you'd be better picking up the correct tool in the first place.