GLM-OCR is an open-source multimodal optical character recognition (OCR) model built on a GLM-V encoder–decoder foundation that brings robust, accurate document understanding to complex real-world layouts and modalities. Designed to handle text recognition, table parsing, formula extraction, and general information retrieval from documents containing mixed content, GLM-OCR excels across major benchmarks while remaining highly efficient with a relatively compact parameter size (~0.9B), enabling deployment in high-concurrency services and edge environments. The model’s multimodal capabilities allow it to reason across image and text content holistically, capturing structured and unstructured information from pages that include dense tables, seals, code snippets, and varied document graphics. GLM-OCR integrates a comprehensive SDK and inference toolchain that makes it easy for developers to install, invoke, and embed into production pipelines with simple commands or APIs.

Features

  • Multimodal OCR for text, tables, and formulas
  • High accuracy on complex documents and benchmarks
  • Efficient deployment for high-throughput systems
  • Comprehensive SDK and simple integration toolchain
  • Support across vLLM, SGLang, Ollama, and transformers
  • Open-source and production-ready for automation pipelines

Project Samples

Project Activity

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Categories

OCR, AI Models

License

Apache License V2.0

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Additional Project Details

Programming Language

Python

Related Categories

Python OCR Software, Python AI Models

Registered

6 days ago