Alternatives
Products that do what GLM-OCR does
GLM-OCR: An online OCR focused on document structure
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Jan 2026 · github.com
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Hi HN, I’ve been working on an OCR pipeline specifically optimized for machine learning dataset preparation. It’s designed to process complex academic materials — including math formulas, tables, figures, and multilingual text — and output clean, structured formats like JSON and Markdown. Some features: • Multi-stage OCR combining DocLayout-YOLO, Google Vision, MathPix, and Gemini Pro Vision • Extracts and understands diagrams, tables, LaTeX-style math, and multilingual text (Japanese/Korean/English) • Highly tuned for ML training pipelines, including dataset generation and…
2025 · github.com
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This started out as a weekend hack with gpt-4-mini, using the very basic strategy of "just ask the ai to ocr the document". But this turned out to be better performing than our current implementation of Unstructured/Textract. At pretty much the same cost. I've tested almost every variant of document OCR over the past year, especially trying things like table / chart extraction. I've found the rules based extraction has always been lacking. Documents are meant to be a visual representation after all. With weird layouts, tables, charts, etc. Using a vision model just make sense! In…
2024 · github.com
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I've developed a Python API service that uses GPT-4o for OCR on PDFs. It features parallel processing and batch handling for improved performance. Not only does it convert PDF to markdown, but it also describes the images within the PDF using captions like `[Image: This picture shows 4 people waving]`. In testing with NASA's Apollo 17 flight documents, it successfully converted complex, multi-oriented pages into well-structured Markdown. The project is open-source and available on GitHub. Feedback is welcome.
2024 · github.com
- 13OB
OCR/Document extraction field has seen lot of action recently with releases like Mixtral OCR, Andrew Ng's agentic document processing etc. Also there are several benchmarks for OCR, however all testing for something slightly different which make good comparison of models very hard. To give an example, some models like mixtral-ocr only try to convert a document to markdown format. You have to use another LLM on top of it to get the final result. Some VLM’s directly give structured information like key fields from documents like invoices, but you have to either add business rules on top…
2025 · nanonets.com
- 14OA
I built OCR Arena as a free playground for the community to compare leading foundation VLMs and open-source OCR models side-by-side. Upload any doc, measure accuracy, and (optionally) vote for the models on a public leaderboard. It currently has Gemini 3, dots.ocr, DeepSeek, GPT5, olmOCR 2, Qwen, and a few others. If there's any others you'd like included, let me know!
Nov 2025 · ocrarena.ai
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2025 · trycardinal.ai
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2024 · github.com
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