Run dots.mocr Using Pinokio No Python Required

The most rapid route to a local installation of this model is through WSL2.

Check out the detailed setup guide below to begin.

The tool automatically synchronizes and downloads the model database.

There is no manual tuning required; the builder deploys the best matching configuration.

🔒 Hash checksum: 2f9c066f6b6097fe1806c08ea2389aa5 • 📆 Last updated: 2026-06-30



  • Processor: Intel i5 or AMD Ryzen 5 for basic 7B models
  • RAM: 64 GB to avoid OOM crashes on large contexts
  • Disk: high-speed SSD 120 GB to cache model layers
  • GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats

The dots.mocr model is a state‑of‑the‑art multimodal OCR system designed for high‑speed document processing. It combines vision and language modules to extract text from scanned images, handwritten notes, and natural‑scene photos with unprecedented accuracy. With a parameter count of 1.5 B, the model runs efficiently on consumer GPUs while maintaining real‑time inference speeds. The architecture incorporates a novel attention‑based layout analyzer that preserves structural relationships, enabling downstream tasks such as data entry and content summarization. dots.mocr also supports multilingual scripts, achieving over 90 % word‑error‑rate reduction on benchmark datasets compared to legacy solutions. Its modular design allows developers to fine‑tune specific components, making it a versatile choice for enterprise workflow automation.

Spec Value
Parameters 1.5 B
Input Types PDF, JPG, PNG, Handwritten
Supported Languages 100
Inference Speed >30 fps on RTX 3080
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作者 小蜘蛛

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