TimmyOVO/deepseek-ocr.rs

Health v2 · maintenance only

Adoption not part of the score

2182 stars · 169 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A Rust implementation of the DeepSeek-OCR inference stack with multiple OCR/VLM backends (DeepSeek-OCR, PaddleOCR-VL, DotsOCR), DSQ quantization, a fast CLI, and an OpenAI-compatible HTTP server. It runs locally on CPU, Apple Metal, or CUDA without any Python runtime, built on Candle and Rocket.

Use cases

• extract text from images and scanned documents locally
• run OCR without installing Python or conda
• serve an OpenAI-compatible OCR API endpoint
• convert PDFs and documents to markdown with layout awareness
• run vision-language models on Apple Silicon with Metal
• batch OCR on CPU-only machines with low memory
• embed OCR inference into native Rust applications

When to choose

• you need local, Python-free OCR inference in Rust
• you want an OpenAI-compatible serving layer for OCR models
• you're on Apple Silicon or have a decent GPU and want high-fidelity document understanding
• you need a CLI for quick one-off OCR tasks

When to avoid

• you need the broadest model ecosystem of Python/HuggingFace Transformers
• you only have limited RAM and need DotsOCR's heavy vision tower
• you need managed/cloud OCR services rather than self-hosted inference

Facets

library · maturity active

ocr llm-inference cli http-server machine-learning computer-vision image-processing pdf developer-tools machine-learning rust windows cli deepseek-ocr paddleocr-vl dotsocr candle openai-compatible-api vision-language-models quantization dsq document-understanding local-inference natural-language-processing macos linux gpu

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