Its errors are interesting (averaging around one per paragraph). Semantically-correct, but wrong on precision (simple example, the English word "ardour" is transcripted as "ardor", and a foreign word like "palazzo" which is intended to remain so, is translated to "palace"). I'm still messing with temp/presence/frequency/top-p/top-k/prompting to see if I can squeeze some more precision out of it, but I'm running out of time.

Not sure if it matters but I exported a PDF page as a PNG with 200dpi resolution, and used that.

It seems like it's reading the text but getting the details wrong.

I would not be comfortable using this in an official capacity without more accuracy. I could see using this for words that another OCR system is uncertain about, though, as a fallback.