dots.ocr's core technological strengths lie in three main areas:
- single-model multitasking: A 1.7B parameter-based visual-linguistic model (VLM) that eliminates the need for a traditional multi-model pipeline and switches tasks such as layout detection and content recognition by changing only the input cues.
- Excellent performance: State-of-the-art in benchmarks such as OmniDocBench, especially in text/table parsing and reading order optimization, significantly outperforming similar tools.
- Highly effective reasoning skills: Although the number of parameters is only 1.7B, with the optimized model architecture and vLLM deployment scheme, the inference speed exceeds that of many large models and is suitable for real production environment applications.
This answer comes from the articledots.ocr: a unified visual-linguistic model for multilingual document layout parsingThe
































