MinerU vs STORM
Side-by-side comparison of two AI agent tools
Short answer
- STORM has had no commit in 12 months; MinerU is actively maintained (905 commits in the last 90 days).
- MinerU is growing faster: +3,746 GitHub stars in the last 30 days vs +558 for STORM.
- Pick MinerU for: transforms complex documents like PDFs into LLM-ready markdown/JSON for your Agentic workflows. Pick STORM for: an LLM-powered knowledge curation system that researches a topic and generates a full-length report.
From GitHub data refreshed daily.
MinerUfree
Transforms complex documents like PDFs into LLM-ready markdown/JSON for your Agentic workflows.
STORMopen-source
An LLM-powered knowledge curation system that researches a topic and generates a full-length report with citations.
Metrics
| MinerU | STORM | |
|---|---|---|
| Stars | 81.0k | 31.6k |
| Star velocity /mo | 3.7k | 558.0952380952382 |
| Commits (90d) | 905 | 0 |
| Releases (6m) | 10 | 0 |
| Overall score | 0.8909026784171507 | 0.3758979607278819 |
Pros
- +专门针对 LLM 优化的输出格式,确保转换后的 Markdown/JSON 能够被 AI 模型高质量理解和处理
- +支持复杂 PDF 文档的结构化解析,保持表格、图像和文本布局的完整性
- +提供 Python SDK 和 Web 应用双重接口,既适合程序化集成也支持交互式使用
- +Automated multi-perspective research that synthesizes information from diverse Internet sources into structured, Wikipedia-style articles with proper citations
- +Human-AI collaborative features through Co-STORM enable interactive knowledge curation with user guidance and preferences
- +Flexible architecture supporting multiple language models, search engines, and document sources through modular components and extensive customization options
Cons
- -主要专注于 PDF 处理,对其他文档格式的支持可能有限
- -复杂文档的处理质量可能依赖于原始文档的质量和结构清晰度
- -大规模批量处理时可能需要考虑计算资源和处理时间的平衡
- -Cannot produce publication-ready articles and requires significant manual editing and fact-checking before professional use
- -Quality and accuracy depend heavily on the underlying language model and search results, potentially leading to inconsistencies or outdated information
- -Complex setup and configuration may be challenging for non-technical users despite simplified installation options
Use Cases
- •构建 RAG(检索增强生成)系统时,将企业内部 PDF 文档转换为向量数据库可索引的格式
- •为 AI 代理开发智能文档分析功能,自动提取和结构化合同、报告中的关键信息
- •建立知识管理系统,将历史文档资料转换为可搜索和可查询的结构化数据
- •Pre-writing research assistance for Wikipedia editors and content creators who need comprehensive topic overviews before manual article development
- •Academic research synthesis for students and researchers who need to quickly gather and organize information from multiple sources on specific topics
- •Knowledge base generation for organizations that need to create structured reports from internal documents and external sources
FAQ
- Which is more popular, MinerU or STORM?
- MinerU has more GitHub stars (80,986 vs 31,555).
- Which is more actively developed, MinerU or STORM?
- MinerU had more commits in the last 90 days (905 vs 0).
- Should I use MinerU or STORM?
- Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.