MinerU HTML

MinerU HTML is a specialized tool that leverages small language models (SLMs) to extract clean, structured HTML bodies from complex web pages. Designed for developers building deep research agents, RAG applications, or large-scale training data pipelines, it processes messy HTML—including forums, Q&A sites, tables, code blocks, and mathematical formulas—and outputs high-fidelity content while preserving structural integrity. Unlike generic web scrapers, MinerU HTML uses a semantic-aware pipeline that understands page layout and content hierarchy, ensuring only the main content is retained. It excels on challenging page types where traditional extraction fails, such as pages with mixed content, heavy ads, or complex formatting. The extracted output is ready for downstream use in language model training or retrieval systems, with proven improvements in benchmark accuracy when used for pretraining. Users can upload HTML files via the web interface for real-time processing; the underlying pipeline is optimized for speed and reliability. The tool is part of the AICC dataset ecosystem, which focuses on high-quality web data processing. It is freely accessible online, with no API or bulk processing endpoints documented. Its main differentiator is the use of SLMs to understand page semantics, rather than relying solely on heuristic or regex-based extraction. MinerU HTML is best suited for data engineers, ML researchers, and developers who need reliable extraction from diverse web sources. It is not designed for visual rendering, interactive browsing, or large-scale automated crawling. Compared to tools like Trafilatura or readability, MinerU HTML offers superior preservation of code blocks, formulas, and tables, but lacks integration support and API access.