📄 中文摘要
文档处理长期以来面临二元选择：使用传统OCR以获得速度和可靠性，或使用AI视觉模型以实现理解。这种将两者视为竞争的方法是错误的。现代文档处理系统最佳的做法是将两者结合。传统OCR擅长于高准确率和低计算成本地提取原始文本，而视觉语言模型（VLM）则能够理解布局、检测样式和重建文档结构。这并不是一场竞争，而是一个技术栈的组合。
OCR与VLM：为何两者兼具至关重要（以及混合方法如何胜出）
出处: OCR vs VLM: Why You Need Both (And How Hybrid Approaches Win)
发布: 2026年3月19日
📄 English Summary
OCR vs VLM: Why You Need Both (And How Hybrid Approaches Win)
Document processing has been traditionally viewed as a binary choice between using conventional OCR for speed and reliability or employing AI vision models for comprehension. This perspective is flawed. The most effective document processing systems today integrate both approaches. Traditional OCR excels at accurately extracting raw text with minimal computational cost, while Vision Language Models (VLMs) address the limitations of OCR by understanding layout, detecting styles, and reconstructing document structure. This is not a competition; it is a technological stack.