zai-org/GLM-OCR
GLM-OCR: Accurate × Fast × Comprehensive
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
Ranks #407 of 2,845 repositories GStars tracks this week (top 14%).
No releases in the last 90 days; the most recent was 189 days ago, with 15 contributors on GitHub.
Use Cases & Benefits
- Provides a multimodal OCR system for accurate and fast document text extraction and layout understanding using GLM-V architecture.
- Delivers state-of-the-art accuracy with efficient inference optimized for complex layouts and real-world business scenarios.
- Use for extracting structured data from complex documents including tables, formulas, and code-heavy pages.
- Use for deploying scalable OCR services with low latency on cloud or edge devices using vLLM, SGLang, or Ollama.
- Use for integrating OCR into production pipelines with easy SDK usage, CLI tools, and flexible configuration options.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
Apache 2.0
Permissive: commercial use, modification and redistribution are allowed with attribution; includes an explicit patent grant from contributors.
Community files
- README: present
Watch-outs
No watch-outs from GStars' checks.
General guidance from repository metadata, not legal advice. How we score
From the README
GLM-OCR is a multimodal OCR model for complex document understanding, built on the GLM-V encoder–decoder architecture. It introduces Multi-Token Prediction (MTP) loss and stable full-task reinforcement learning to improve training efficiency, recognition accuracy, and generalization. The model integrates the CogViT visual encoder pre-trained on large-scale image–text data, a lightweight cross-modal connector with efficient token downsampling, and a GLM-0.5B language decoder. Combined with a two-stage pipeline of layout analysis and parallel recognition based on PP-DocLayout-V3, GLM-OCR delivers robust and high-quality OCR performance across diverse document layouts.
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
Forks
670+21
Open issues
66+21
Compared with peers in Computer Vision
Fastest-growing repositories GStars tracks in this cohort for the week of Oct 11, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| koharu-rs/koharu | 6.4K | +483 | 63 | 30 days ago |
| PaddlePaddle/PaddleOCR | 91.0K | +0 | 75 | 123 days ago |
| microsoft/AI-For-Beginners | 69.8K | +0 | 45 | — |
| opendataloader-project/opendataloader-pdf | 29.7K | +0 | 75 | 2 days ago |
| memvid/memvid | 16.6K | +0 | 75 | 138 days ago |
| zai-org/GLM-OCR | 7.5K | +0 | 75 | 189 days ago |
| Category median | 29.7K | +0 | 75 | — |
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