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Show HN: Qwen-2.5-32B is now the best open source OCR model

(github.com)
208 points themanmaran | 2 comments | 01 Apr 25 17:00 UTC | HN request time: 0s | source

Last week was big for open source LLMs. We got:

- Qwen 2.5 VL (72b and 32b)

- Gemma-3 (27b)

- DeepSeek-v3-0324

And a couple weeks ago we got the new mistral-ocr model. We updated our OCR benchmark to include the new models.

We evaluated 1,000 documents for JSON extraction accuracy. Major takeaways:

- Qwen 2.5 VL (72b and 32b) are by far the most impressive. Both landed right around 75% accuracy (equivalent to GPT-4o’s performance). Qwen 72b was only 0.4% above 32b. Within the margin of error.

- Both Qwen models passed mistral-ocr (72.2%), which is specifically trained for OCR.

- Gemma-3 (27B) only scored 42.9%. Particularly surprising given that it's architecture is based on Gemini 2.0 which still tops the accuracy chart.

The data set and benchmark runner is fully open source. You can check out the code and reproduction steps here:

- https://getomni.ai/blog/benchmarking-open-source-models-for-...

- https://github.com/getomni-ai/benchmark

- https://huggingface.co/datasets/getomni-ai/ocr-benchmark

Show context
azinman2 ◴[01 Apr 25 20:05 UTC] No.43550807[source]▶
News update: OCR company touts new benchmark that shows its own products are the most performant.
replies(3): >>43550853 #>>43551091 #>>43551815 #
kapitalx ◴[01 Apr 25 22:05 UTC] No.43551815[source]▶
To be fair, they didn't include themselves at all in the graph.
replies(1): >>43552117 #
1. azinman2 ◴[01 Apr 25 22:52 UTC] No.43552117[source]▶
They did. It’s in the #1 spot

Update: looks like the removed themselves from the graph since I saw it earlier today!

replies(1): >>43552236 #
2. axpy906 ◴[01 Apr 25 23:06 UTC] No.43552236[source]▶
Yup, they did.

The beauty of version control: https://github.com/getomni-ai/benchmark/commit/0544e2a439423...