Wouldn't "Serverless OCR" mean something like running tesseract locally on your computer, rather than creating an AI framework and running it on a server?

How does this compare to Tesserect?

Slight tangent: i was wondering why DeepSeek would develop something like this. In the linked paper it says

> In production, DeepSeek-OCR can generate training data for LLMs/VLMs at a scale of 200k+ pages per day (a single A100-40G).

That... doesn't sound legal

Question for the crowd -- with autoscaling, when a new pod is created it will still download the model right from huggingface?

I like to push everything into the image as much as I can. So in the image modal, I would run a command to trigger downloading the model. Then in the app just point to the locally downloaded model. So bigger image, but do not need to redownload on start up.

Deepseek OCR is no longer state of the art. There are much better open source OCR models available now.

ocrarena.ai maintains a leaderboard, and a number of other open source options like dots [1] or olmOCR [2] rank higher.

[1] https://www.ocrarena.ai/compare/dots-ocr/deepseek-ocr

[2] https://www.ocrarena.ai/compare/olmocr-2/deepseek-ocr