Prolog night be interesting because I bet nobody is trying to train very hard on it, but I'm less directly interested in model performance with Prolog.
A relative lack of training data might have a bigger effect though.
a) Typed Racket
b) OCaml
c) Julia
I would love to see those three added to your benchmarks. And Mistral Medium 3.5 added to the LLM list, please.
Mistral Medium 3.5 is on there, but you will have to scroll down pretty far to find it (does not perform well): https://gertlabs.com/rankings?mode=oneshot_coding
Typed Racket is to Racket as TypeScript is to JavaScript: it adds some additional static checks to an otherwise dynamic language via gradual typing. This pair of languages might help begin answer the question "does gradual typing generally help LLMs, or does TypeScript outperform JavaScript for incidental reasons?".
Among Lisps, I'm most interested in seeing Clojure because it's a language I can see myself using with LLMs at work. But Typed Racket and Racket could make an especially interesting pair because of the gradual typing thing.
I'm not sure whether you want to include them in your project. The kind of selectivity you describe yourself as going for is hard for me, especially since I'm not the one doing the work. :)
PS: Aside from this benchmarking and comparison project: Racket is an interesting language and seems like a good place to start if you want to explore classic Scheme texts (Structure and Interpretation of Computer Programs, The Little Schemer, How to Design Programs) or newer ones that try to teach newer or more specialized ideas (e.g., The Little Typer). You may have to tweak the language a bit to stay faithful to some of those books, but that's something Racket is good at and there are already sources noting relevant differences online.
When a non-programmer in my life expressed curiosity about programming, we ended up starting HtDP together and it's been fun. I think Racket was a good choice for that.
Just want to be sure I'm reading the results correctly... When I compare GPT-5.5 with Mistral Medium 3.5, I see in the tables:
a) Mistral beats GPT in Java and C++
b) It's close for Rust
c) GPT-5.5 easily wins for Go, Javascript, Python and Typescript
Model choice really does appear to be language dependent (assuming I'm reading the results correctly).
The Qwen3.6 models have memorized some common games. For example, if you ask it to create an index.html with a snake game, it will generate almost the same high quality snake game every time. The relatively low success rate of 25% but high average percentile of almost 100% for one-shot coding in Python suggests that the model is extremely good at few tasks.
- Haskell
- OCaml
- F#
- Scala
- Gleam
- Purescript
- Grain
- Idris
Then I asked if there were any Schemes or Lisps that met the initial requirements, which added a bunch more options (Typed Racket, Typol, Elm, ReScript etc).
Then I asked about Julia specifically, as it's a language I'm already reasonably familiar with and knew that it's possible to write it with static annotations.
Next I started filtering the list based on additional criteria; didn't want to target a JS compilation target, performance, size of package ecosystem, tooling, community, learning curve (I do want to review and understand the output).
There were a bunch of follow-up questions over a few hours of prompting, reading and a couple of beers. All this resulted in the shortlist of OCaml, Typed Racket and Julia.
Julia pretty much remains in there, even though it doesn't really meet the strongly typed initial criteria, based on my familiarity, the ecosystem especially for AI/ML tasks and performance factors.
I know zero about OCaml and find the thought of learning it a bit daunting. Typed Racket seems more approachable anyway.