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DeepSeek OCR

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990 points pierre | 1 comments | 20 Oct 25 06:26 UTC | HN request time: 0s | source
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pietz ◴[20 Oct 25 08:49 UTC] No.45641449[source]▶
My impression is that OCR is basically solved at this point.

The OmniAI benchmark that's also referenced here wasn't updated with new models since February 2025. I assume that's because general purpose LLMs have gotten better at OCR than their own OCR product.

I've been able to solve a broad range of OCR tasks by simply sending each page as an image to Gemini 2.5 Flash Lite and asking it nicely to extract the content in Markdown under some additional formatting instructions. That will cost you around $0.20 for 1000 pages in batch mode and the results have been great.

I'd be interested to hear where OCR still struggles today.

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1. themanmaran ◴[20 Oct 25 22:11 UTC] No.45650079[source]▶
> OmniAI benchmark that's also referenced here wasn't updated with new models since February 2025. I assume that's because general purpose LLMs have gotten better at OCR than their own OCR product.

Benchmark author here. No, just pivoted away from OCR API as a product! Still use our API internally but have been lazy about updating benchmarks.

Gemini is definitely the best model for OCR. But it has a really high rate of "recitation" errors. Where it will determine the output token is too close to its training data and cut it off. Something like 10% of the time from our testing. Also it has this hilarious hallucination when you have a blank page in the document mix and it just makes up new info.

OpenAI is OK. GPT5 wasn't any better than 4o or 4.1. Main issues were: dropping content like headers/footers, loses it's mind on sideways pages, and will frequently refuse to read things like ID documents, health care forms, or things it judges to have too much PII.