The "minimum viable product" is part of the development process. If you are already at a certain quality and choose to make it worse, this is something else. Enshittification or just greed come to my mind.
Be careful with that, numpy arrays can be slower than Python tuples for some operations. The creation is always slower and the overhead has to be worth it.
Every time I see a table like this numbers go up. Can someone explain what this actually means? Is there just an improvement that some tests are solved in a better way or is this a breakthrough and this model can do something that all others can not?