Yet: how is pricing? Evaluating contents and routing appropriately isn't a new challenge in OCR, one of the oldest fields of applications in ML. Thus, how do the smaller open models perform in tandem with relatively pricy $/pg models & APIs? Your use case is remarkably rare relative to the volume and price sensitivity of enterprise data warehouse ops.
The big difference is traditional OCR used basic pattern matching to find text, whereas models like Mistral OCR (and GPT, etc) use computer vision instead and deep learning to parse text, math equations, and apparently in some cases extract images too.
I'd love to see some advancements in traditional OCR based on ideas and concepts we've learned from newer "OCR-like" models since traditional OCR is drastically cheaper.