{"repo":"TimmyOVO/deepseek-ocr.rs","free":true,"listed":false,"github":"https://github.com/TimmyOVO/deepseek-ocr.rs","clone":"git clone https://github.com/TimmyOVO/deepseek-ocr.rs.git","description":"Rust multi‑backend OCR/VLM engine (DeepSeek‑OCR-1/2, PaddleOCR‑VL, DotsOCR) with DSQ quantization and an OpenAI‑compatible server & CLI – run locally without Python.","language":"Rust","stars":2180,"topics":["candle","ocr","ocr-recognition","openai","rust"],"license":"Apache-2.0","category":"media-processing","readme_excerpt":"deepseek-ocr.rs 🚀 Rust implementation of the DeepSeek-OCR inference stack with a fast CLI and an OpenAI-compatible HTTP server. The workspace packages multiple OCR backends, prompt tooling, and a serving layer so you can build document understanding pipelines that run locally on CPU, Apple Metal, or (alpha) NVIDIA CUDA GPUs. 中文文档请看 README CN.md。 Want ready-made binaries? Latest macOS (Metal-enabled) and Windows bundles live in the build-binaries workflow artifacts. Grab them from the newest green run. Choosing a Model 🔬 Model Memory footprint Best on When to pick it --- --- --- --- DeepSeek‑OCR ≈6.3GB FP16 weights, ≈13GB RAM/VRAM with cache & activations (512-token budget) Apple Silicon + Metal (FP16), high-VRAM NVIDIA GPUs, 32GB+ RAM desktops Highest accuracy, SAM+CLIP global/local context, MoE DeepSeek‑V2 decoder (3B params, 570M active per token). Use when latency is secondary to quality. PaddleOCR‑VL ≈4.7GB FP16 weights, ≈9GB RAM/VRAM with cache & activations 16GB laptops, CPU-only boxes, mid-range GPUs Dense 0.9B Ernie decoder with SigLIP vision tower. Faster startup, lower memory, great for batch jobs or lightweight deployments. DotsOCR ≈9GB FP16 weights, but expect 30–50GB RAM/VRAM for high-res docs due to huge vision tokens Apple Silicon + Metal BF16, ≥24GB CUDA cards, or 64GB RAM CPU workstations Unified VLM (DotsVision + Qwen2) that nails layout, reading order, grounding, and multilingual math if you can tolerate the latency and memory bill. \\ Measured from the de","default_branch":null,"files":null,"tree":[],"storefront":"/r/TimmyOVO","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/TimmyOVO/deepseek-ocr.rs/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}