Readit Newsadammajcher commented on Show HN: Ocrbase – pdf → .md/.json document OCR and structured extraction API github.com/majcheradam/oc... · Posted by u/adammajcher
Why is 12GB+ VRAM a requirement? The OCR model looks kind of small, https://huggingface.co/PaddlePaddle/PaddleOCR-VL/tree/main, so I'm assuming it is some processing afterwards it would be used for.
fixed
Is only bun supported or also regular node?
it's bun first because of performance
Sure. The self host guide tells me to enter my github secret, in plain-text, in an env file. But it doesn't tell me why I should do that.
Do people actually store their secrets in plain text on the file system in production environments? Just seems a bit wild to me.
well, you can use secrets manager as well
This is admittedly dated but even back in December 2023 GPT-4 with it's Vision preview was able to very reliably do structured extraction, and I'd imagine Gemini 3 Flash is much better than back then.
https://binal.pub/2023/12/structured-ocr-with-gpt-vision/
Back of the napkin math (which I could be messing up completely) but I think you could process a 100 page PDF for ~$0.50 or less using Gemini 3 Flash?
>560 input tokens per page * 100 pages = 56000 tokens = $0.028 input ($0.5/m input tokens) >~1000 output tokens per page * 100 pages = $0.30 output ($3/m output tokens)
(https://ai.google.dev/gemini-api/docs/gemini-3#media_resolut...)
sure, in some small projects I recommend my friends to use gemini 3 flash. ocrbase is aimed more at scale and self-hosting: fixed infra cost, high throughput, and no data leaving your environment. at large volumes, that tradeoff starts to matter more than per-100-page pricing