docling vs GLM-OCR
Document parsing and OCR projects compared
docling converts many document and media formats into structured content for downstream workflows. GLM-OCR focuses on recognizing text and layout in document images and PDFs, with hosted and self-hosted inference options.
docling: Convert Documents into Structured Content
Docling parses documents such as PDFs, Word files, spreadsheets, and images into structured content for applications and generative AI workflows. It offers local processing, a Python library, and a command-line interface.
GLM-OCR: Recognize Text and Structure in Documents
GLM-OCR is a multimodal OCR model and SDK for extracting text and layout from complex documents. Use it through a hosted API or deploy the pipeline with supported inference servers for local control.
| docling | GLM-OCR | |
|---|---|---|
| Language | Python | Python |
| License | MIT | Apache-2.0 |
| Stars | 68.7k | 7.5k |
| Forks | 5k | 669 |
| Last analyzed | Oct 12, 2026 | Oct 3, 2026 |
Key differences
- docling handles formats including office files, HTML, images, and audio; GLM-OCR processes images and PDFs.
- docling offers exports including Markdown, HTML, WebVTT, and lossless JSON; GLM-OCR returns Markdown and JSON layout details.
- docling can run locally, including in air-gapped environments; GLM-OCR offers hosted API access or self-hosting with supported inference servers.
- docling is MIT licensed; GLM-OCR's repository code is Apache-2.0, while its README identifies different licenses for the model and an integrated component.
- docling has 68.3k stars and 5k forks; GLM-OCR has 7.5k stars and 669 forks.
- docling supports integrations with LangChain, LlamaIndex, Haystack, and Crew AI; GLM-OCR provides a Flask service and modular components for custom pipelines.
Choose docling if you…
- need to ingest a broad mix of document and media formats.
- want local processing, including in air-gapped environments.
- plan to use integrations with retrieval and AI frameworks.
Choose GLM-OCR if you…
- need text and layout recognition focused on images and PDFs.
- want a choice between hosted API access and self-hosted inference.
- plan to deploy OCR as a service or customize a pipeline with modular components.
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This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.