What are Mistrals strengths and weaknesses? I tried it for infrastructure as code and it wasn't able to output more than the most basic examples, let alone modify them.
In my experience most open source models do quite well with Python and Javascript, but don't perform so well when it comes to other languages and the usage of their special characteristics (e.g. it will still be able to write simple control flow in Rust, but probably not use async/await correctly).
I've tried using LLMs in general with IaC (K8s resources/Helm charts), and they all did well when asking it a very specific thing about it (e.g. "Is there an alternative way to accomplish X?"), but also never had it perform well when outputting YAML directly (either from scratch of modifying it).
Give zephyr a try (available in ollama and similar places)
It's a fine tune of mistral and works quite well.
But as you point out, these models have less general knowledge compared to their massive siblings. Knowledge based queries are going to be lower quality than using gpt-4.
Pretty good at instructions
Uncensored, no RHLF bs
Anyway, to answer your question: https://ollama.ai/