dots.mocr For Low VRAM (6GB/8GB) Easy Build

The shortest path to running this model is by activating Hyper-V features.

Check out the detailed setup guide below to begin.

Be patient as the system self-retrieves massive model weights dynamically.

The setup file includes a feature that instantly optimizes all configurations.

📘 Build Hash: 0976938f39d580ed0ffdab7fdb7b2298 • 🗓 2026-06-30



  • CPU: multi-threading optimized for fast prompt processing
  • RAM: at least 32 GB in dual-channel mode for bandwidth
  • Disk Space: required: fast PCIe 4.0 drive for instant boots
  • Graphics: TensorRT-LLM / vLLM inference engine compatible chip

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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