Huge thanks to @atomic_chat_hq for the awesome demo! 🙌
摘要
非常感谢 @atomic_chat_hq 的精彩演示！🙌 他们在 M5 Max MacBook 上本地运行 MiniCPM-OCR 1.0，处理了 Anthropic S-1 文件的全部 415 页——模型仅 1.2GB，每页约 4 秒，零数据离开设备。 小模型，严肃的文档理解，完全本地。🔥
摘要由模型根据原文撰写，以原文为准。
正文 · 原文
Huge thanks to @atomic_chat_hq for the awesome demo! 🙌
They ran MiniCPM-OCR 1.0 locally on an M5 Max MacBook to process all 415 pages of Anthropic’s S-1 filing — with a 1.2GB model, ~4 seconds per page, and zero data leaving the device.
Small model, serious document understanding, fully local. 🔥
A 1.2GB model on a Mac read Anthropic's whole IPO 📄 @OpenBMB MiniCPM-OCR 1.0 went through all 415 pages of Anthropic's S-1 on an M5 Max MacBook at about 4 seconds a page and nothing ever left the laptop GGUFs -> https://huggingface.co/AtomicChat/MiniCPM-OCR-1.0-GGUF在 X 查看被引用的帖子
来源：OpenBMB · x.com
引用原文
OpenBMB. Huge thanks to @atomic_chat_hq for the awesome demo! 🙌[EB/OL]. (2026-10-28)[访问日期]. https://x.com/OpenBMB/status/2115433341226745861.