dots.mocr Locally (No Cloud)

Deploying this model locally is quickest when done via a simple curl command.

Please follow the instructions listed below to get started.

The setup auto-downloads all needed files (several GBs).

Once launched, the wizard detects your specs to configure the model for maximum efficiency.

🧩 Hash sum → 1762f19a435c635346b2c9624499d89f — Update date: 2026-06-24 Verify CPU: 8-core / 16-thread recommended for orchestration RAM: fast 5600MHz+ required to avoid memory bottlenecks Disk Space: 100 GB for multi-modal model vision components Graphics: stable 30+ tk/s at 4-bit quantization on medium setup

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.

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