Setup dots.mocr

To get this model running locally in no time, utilize the built-in WSL tools.

Refer to the instructions below to proceed.

The installer auto-downloads and deploys the entire model pack.

The program scans your VRAM and RAM to seamlessly apply optimal configurations.

🛠 Hash code: 7cff3fd3618ffa387bedff9e3440e01d — Last modification: 2026-07-05



  • Processor: Intel i7 / Ryzen 7 for heavy Quantized models
  • RAM: 32 GB highly recommended for 26B+ GGUF models
  • Disk: 150+ GB for high-context vector database storage
  • GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference

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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