I'm working on a natural language router system that chooses the optimal model for a given language pair. It uses a combination of RLHF and conventional translation scoring. I envision it to soon become the cheapest translation service providing the highest average quality across languages by striking a balance between Google Translate's expensive API and any given, cheaper, random model's performance across different languages.

I'll beginning to integrate it into my user-facing application for language learners soon: www.abal.ai