Using Docker is the absolute quickest way to install this model on your local machine.
Follow the guidelines below to continue.
Next, execute the setup script or run docker-compose.
🛠 Hash code: 3d599715138ce21a2a43723bb0516cad — Last modification: 2026-06-21
- Processor: high single-core performance needed for token latency
- RAM: high-speed DDR5 memory preferred for CPU offloading
- Disk: 150+ GB for high-context vector database storage
- Graphics: TensorRT-LLM / vLLM inference engine compatible chip
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DeepSeek-OCR is a state‑of‑the‑art optical character recognition model that delivers high accuracy across a wide range of fonts and languages. It leverages a deep convolutional neural network combined with a transformer‑based sequence decoder to achieve real‑time processing while preserving fine‑grained spatial information. The model supports multilingual text extraction, handling scripts from Latin, Cyrillic, Arabic, Chinese, and many others without requiring separate language packs. Its architecture incorporates adaptive pooling and attention mechanisms that reduce errors on skewed or low‑resolution documents. A dedicated post‑processing module normalizes whitespace and corrects common OCR mistakes, ensuring clean output for downstream applications. Developers can easily integrate DeepSeek-OCR into existing workflows via a lightweight SDK that provides both cloud and on‑device inference options.
| Feature |
Specification |
| Supported Languages |
100+ |
| Processing Speed |
>200 FPS |
| Accuracy (standard benchmark) |
99.2% |
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