dots.ocr

Model · Image and text to text

dots.mocr

Dots Studio

dots.mocr We present dots.mocr. Beyond achieving state-of-the-art (SOTA) performance in standard multilingual document parsing among models of comparable size, dots.mocr excels at converting structured graphics (e.g., charts, UI layouts, scientific figures and etc.) directly into SVG code. Its core capabilities encompass grounding, recognition, semantic understanding, and interactive dialogue. Simultaneously, we are releasing dots.mocr-svg, a variant specifically optimized for robust image-to-SVG parsing tasks. More information can be found in the paper. Visual languages (e.g., charts, graphics, chemical formulas, logos) encapsulate dense human knowledge. dots.mocr unifies the…

Model · Image and text to text

DeepSeek-OCR

DeepSeek

Inference using Huggingface transformers on NVIDIA GPUs. Requirements tested on python 3.12.9 + CUDA11.8： Refer to GitHub for guidance on model inference acceleration and PDF processing, etc. [2025/10/23] DeepSeek-OCR is now officially supported in upstream vLLM. We would like to thank Vary, GOT-OCR2.0, MinerU, PaddleOCR, OneChart, Slow Perception for their valuable models and ideas. author={Wei, Haoran and Sun, Yaofeng and Li, Yukun}, year={2025}

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Unlimited-OCR

BAIDU

[2026/07/21] Thanks to the ms-swift community for their support, our model now supports training with ms-swift. - [2026/07/03] Thanks to the Baidu Cloud team for their support. Our model is now available on Baidu Cloud. - [2026/06/28] Thanks to the vLLM community and Tianyu Guo for their support, our model now supports vLLM inference. - [2026/06/24] Thanks to AK for creating a demo for us. It is now available at Hugging Face Spaces. - [2026/06/23] Our paper is now available on arXiv. - [2026/06/23] Thanks to the ModelScope community for their support. Our model is now available at ModelScope. - [2026/06/22] We present Unlimited-OCR, aiming to push Deepseek-OCR one step further. Inference…

baidu/Unlimited-OCR as one repository max serve opens directly on Apple Silicon: baidu's weights unchanged (model.safetensors, byte-identical to upstream at revision 07dea832e22aefee32ad281d4b80551282e1c168, sha256 2bc48a7a110061ea58fff65d3169367eebe3aee371ca6968dc2219c1b2855fc6), the tokenizer files as published, and the checkpoint's config.json with two keys removed (automap, modeltype) so MAX can load it without trustremotecode. The runtime is a MAX custom architecture with two Mojo custom ops, served from https://github.com/kthr/unlimited-ocr-max as an OpenAI-compatible endpoint on the Metal GPU or the CPU. The repository also carries model-int8.safetensors, this port's weight-only int8…

Model · Image and text to text

Unlimited-OCR-AWQ

Sahil Chachra

AWQ 4-bit (W4A16) quantization of baidu/Unlimited-OCR, a 3B vision-language OCR model that pushes DeepSeek-OCR one step further (one-shot, long-horizon document parsing). This repo quantizes the DeepSeek-V2 MoE text decoder with activation-aware scaling (AWQ) while keeping the vision tower in BF16, so it stays a drop-in transformers model. Unlimited-OCR uses the DeepSeek-OCR prompt vocabulary. The prompt must contain; prefix it with whenever you also want bounding boxes for what was read. - base — basesize=1024, imagesize=1024, cropmode=False. Good default for normal pages. - gundam — basesize=1024, imagesize=640, cropmode=True. Tiles the page; use for dense or large/high-resolution…

Model · Image and text to text

DeepSeek-OCR-2

DeepSeek

Inference using Huggingface transformers on NVIDIA GPUs. Requirements tested on python 3.12.9 + CUDA11.8： Refer to GitHub for guidance on model inference acceleration and PDF processing, etc. We would like to thank DeepSeek-OCR, Vary, GOT-OCR2.0, MinerU, PaddleOCR for their valuable models and ideas. We also appreciate the benchmark OmniDocBench. author={Wei, Haoran and Sun, Yaofeng and Li, Yukun}, year={2025} title={DeepSeek-OCR 2: Visual Causal Flow}, author={Wei, Haoran and Sun, Yaofeng and Li, Yukun}, year={2026}