Isn't it better to use an LLM to train modernbert or xgboost et al?
But with Jev you're just paying for input (prefill) which is really fast, and in case of Jev specifically costs 50% of Deepseek V4.1 Flash (which has famously really cheap input token pricing).
I put 250MB / 1M lines of logs through Grev and it cost ~$10USD, DSv4.1 would be at least 10x that and much, much, much slower. With Jev/Grev that 1M requests took 10 mins
Edit: completely misread your question - yeah you could finetune specialized models to do that, probably based on some decent pretrained llm base, that is true for roughly any Jev-shaped problem. Do you want to bother doing that, also having to deal with having to host a zoo of specialized models?