MegaParse vs MinerU

Side-by-side comparison of two AI agent tools

Short answer

  • MegaParse has had no commit in 19 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 +11 for MegaParse.
  • Pick MegaParse for: file Parser optimised for LLM Ingestion with no loss Parse PDFs, Docx, PPTx in a format that is ideal for LLMs. Pick MinerU for: transforms complex documents like PDFs into LLM-ready markdown/JSON for your Agentic workflows.

From GitHub data refreshed daily.

MegaParseopen-source

File Parser optimised for LLM Ingestion with no loss 🧠 Parse PDFs, Docx, PPTx in a format that is ideal for LLMs.

MinerUfree

Transforms complex documents like PDFs into LLM-ready markdown/JSON for your Agentic workflows.

Metrics

MegaParseMinerU
Stars7.4k81.0k
Star velocity /mo11.2698412698412693.7k
Commits (90d)0905
Releases (6m)010
Overall score0.208702585959621850.8909026784171507

Pros

  • +Zero information loss during parsing with specific focus on preserving complex document elements like tables, headers, and images
  • +Superior performance with 0.87 similarity ratio in benchmarks, significantly outperforming competing parsers
  • +Dual parsing modes including MegaParse Vision that leverages advanced multimodal AI models for enhanced document understanding
  • +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

Cons

  • -Requires multiple external dependencies (poppler, tesseract, libmagic on Mac) which can complicate installation
  • -Needs OpenAI or Anthropic API keys for operation, adding ongoing costs for usage
  • -Minimum Python 3.11 requirement may limit compatibility with older environments
  • -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

Use Cases

  • •Preparing documents for RAG (Retrieval-Augmented Generation) systems where preserving all context and formatting is critical
  • •Converting complex academic or business documents with tables and images into LLM-ready format for analysis
  • •Building document processing pipelines that need to maintain fidelity across diverse file formats (PDF, Word, PowerPoint)
  • •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

FAQ

Which is more popular, MegaParse or MinerU?
MinerU has more GitHub stars (80,986 vs 7,415).
Which is more actively developed, MegaParse or MinerU?
MinerU had more commits in the last 90 days (905 vs 0).
Should I use MegaParse or MinerU?
Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.