Comment by klibertp

Scala is explicitly multiparadigm and offers a lot of advanced OOP features. It also had a Python-like (though reportedly better handled) 2 -> 3 transition, which deprecated some things, removed others, and added a bunch of new ones. Scala has always been complex, and right now it's also chaotic. It's a wonder the models can get that high a score with it, honestly.

Racket is a similarly large PL, with many abstractions built on the metaprogramming primitives it offers. Without looking at the generated code, it's hard to say anything, but I suspect the high score despite that might be because of the Scheme core of Racket: `racket/base` is a much smaller language than `racket`, so if the LLMs keep to it, it might narrow the solution space enough to show different results.

In general, I think you're half-right: the "solution space" size is a factor, but so is its shape - ie. which features specifically are offered and how they interact. A more compact and cohesive language design should yield better results than just a reduced surface area. C is not a huge language, but the features it offers don't lend themselves to writing correct code much. Elixir is both relatively small and strongly steers a programmer towards safer idioms. Racket is big, but the advanced features are opt-in, while the baseline (immutable bindings, pure functions, expressive contracts) is similar to Elixir. Python is both huge and complex; "there's one obvious way to do it" has always been a bit of a joke. Rust is incredibly complex - the idea is that the tooling should allow you to handle that complexity easily, but that requires agents; one-shotting solutions there won't work as well.