Same token burn / cost though right?

I think OP's point remains, if you generate 140k pairs, your local model would need to run that many to offset having just used the generator (SOTA or not) model to begin with.

I wonder if another approach if latency is a concern is just to do a two shot pass with Jev (perhaps given small context you'd want one to match command, then one to match args of given command) would be an extremely fast, and cheap way to do it - rather than training your own.