Distilly vs MinerU
Side-by-side comparison of two AI agent tools
Short answer
- MinerU is growing faster: +3,732 GitHub stars in the last 30 days vs +870 for Distilly.
- Pick Distilly for: distilly — Distill how they think into reusable Skills for any Agent or Bot. Pick MinerU for: transforms complex documents like PDFs into LLM-ready markdown/JSON for your Agentic workflows.
From GitHub data refreshed daily.
D
Distillyopen-source
Distilly — Distill how they think into reusable Skills for any Agent or Bot. Formerly Colleague Skill（原同事 Skill）.
MinerUfree
Transforms complex documents like PDFs into LLM-ready markdown/JSON for your Agentic workflows.
Metrics
| Distilly | MinerU | |
|---|---|---|
| Stars | 25.3k | 81.0k |
| Star velocity /mo | 870 | 3.7k |
| Commits (90d) | 31 | 905 |
| Releases (6m) | 0 | 10 |
| Downloads (30d, npm + PyPI) | — | 96.9K |
| Overall score | 0.5714059308804199 | 0.8796799796634358 |
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
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
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
FAQ
- Which is more popular, Distilly or MinerU?
- MinerU has more GitHub stars (81,025 vs 25,262).
- Which is more actively developed, Distilly or MinerU?
- MinerU had more commits in the last 90 days (905 vs 31).
- Should I use Distilly or MinerU?
- Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.