How to Deploy dots.mocr Locally (No Cloud) Windows

If you want the fastest local installation for this model, use standard pip packages.

Make sure to follow the instructions below.

The client handles the setup, pulling gigabytes of data automatically.

The installer diagnoses your environment to deploy the most compatible profile.

🧾 Hash-sum — 8e7f20359d9f2a7cf05d18786531ddf7 • 🗓 Updated on: 2026-06-23



  • Processor: Intel i7 / Ryzen 7 for heavy Quantized models
  • RAM: fast 5600MHz+ required to avoid memory bottlenecks
  • Disk Space: free: 80 GB on system drive for scratch space
  • Graphics: 12 GB VRAM minimum required for basic quantization

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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