Type: Web Article Original Link: https://huggingface.co/ibm-granite/granite-docling-258M Publication Date: 2025-09-22
Summary #
WHAT - Granite Docling is a multimodal Image-Text-to-Text model developed by IBM Research for efficient document conversion. It is based on the IDEFICS architecture, using siglip-base-patch- as the vision encoder and Granite M as the language model.
WHY - It is relevant for business AI because it offers an advanced solution for document conversion, improving accuracy in detecting mathematical formulas and the stability of the inference process.
WHO - The main players are IBM Research, which developed the model, and the Hugging Face community, which hosts the model.
WHERE - It positions itself in the market for multimodal models for document conversion, integrating with Docling pipelines and supporting multiple languages.
WHEN - The model was released in September 2024 and is already integrated into Docling pipelines, indicating initial maturity but with potential for further development.
BUSINESS IMPACT:
- Opportunities: Integration with the existing stack to improve document conversion and multilingual support.
- Risks: Competition with other multimodal models and the need to keep up with technological updates.
- Integration: Possible integration with existing document processing tools to improve accuracy and efficiency.
TECHNICAL SUMMARY:
- Core technology stack: Uses PyTorch, Transformers, and Docling SDK. The model is based on IDEFICS with siglip-base-patch- as the vision encoder and Granite M as the LLM.
- Scalability and limits: Supports inference on single pages and specific regions, but may require optimizations for large volumes of data.
- Technical differentiators: Improved detection of mathematical formulas, stability of the inference process, and support for languages such as Japanese, Arabic, and Chinese.
Use Cases #
- Private AI Stack: Integration into proprietary pipelines
- Client Solutions: Implementation for client projects
- Strategic Intelligence: Input for technological roadmap
- Competitive Analysis: Monitoring AI ecosystem
Resources #
Original Links #
- ibm-granite/granite-docling-258M · Hugging Face - Original link
Article recommended and selected by the Human Technology eXcellence team, processed through artificial intelligence (in this case with LLM HTX-EU-Mistral3.1Small) on 2025-09-22 15:03 Original source: https://huggingface.co/ibm-granite/granite-docling-258M
Related Articles #
- Dolphin: Document Image Parsing via Heterogeneous Anchor Prompting - Python, Image Generation, Open Source
- Dolphin: Document Image Parsing via Heterogeneous Anchor Prompting - Open Source, Image Generation
- dots.ocr: Multilingual Document Layout Parsing in a Single Vision-Language Model - Foundation Model, LLM, Python