> Perhaps these things aren't well represented in the training data for these open models

I know from first-hand experience that at least a couple of the SOTA providers use third-party providers for supervised finetuning with instructions that are heavily geared towards a specific set of languages as well. But of course the base dataset from the major providers is likely to be sufficiently better that it matters less, and the big models are good enough at carrying over training that it at least seems like extra training on the core languages they care about at least somewhat carries over (you see this with natural language too - they do really well for many minor languages that make up a miniscule proportion of the training data).

(I won't say much more regarding the SFT/RLHF work due to NDAs - plural; I know who one of the providers is; I don't know who the one or more others are as the intermediary I did some work for obscured it well enough that I couldn't really violate the NDA even if I wanted to)