Skywork-R1V

📖 Technical Report | 💻 GitHub | 🌐 ModelScope

1. Model Introduction

Model Name	Vision Encoder	Language Model	HF Link
Skywork-R1V-38B	InternViT-6B-448px-V2_5	deepseek-ai/DeepSeek-R1-Distill-Qwen-32B	🤗 Link
Skywork-R1V2-38B	InternViT-6B-448px-V2_5	Qwen/QwQ-32B	🤗 Link

2. Feature

Visual Chain-of-Thought: Enables multi-step logical reasoning on visual inputs, breaking down complex image-based problems into manageable steps.
Mathematical & Scientific Analysis: Capable of solving visual math problems and interpreting scientific/medical imagery with high precision.
Cross-Modal Understanding: Seamlessly integrates text and images for richer, context-aware comprehension.

3. Evaluation

Comparison with Larger-Scale Open-Source and Closed-Source Models

	Benchmark	LLM	VLM
		QwQ-32B-Preview	InternVL-2.5-38B	VILA 1.5-40B	InternVL2-40B	Skywork-R1V-38B
Reasoning	MATH-500	90.6	-	-	-	94.0
	AIME 2024	50.0	-	-	-	72.0
	GPQA	54.5	-	-	-	61.6
Vision	MathVista(mini)	-	71.9	49.5	63.7	67.5
	MMMU(Val)	-	63.9	55.1	55.2	69.0

Evaluation results of state-of-the-art LLMs and VLMs

	Vision	Reasoning			Vision
		MATH-500	AIME 2024	GPQA	MathVista(mini)	MMMU(Val)
		pass@1	pass@1	pass@1	pass@1	pass@1
Qwen2.5-72B-Instruct	❌	80.0	23.3	49.0	-	-
Deepseek V3	❌	90.2	39.2	59.1	-	-
Deepseek R1	❌	97.3	79.8	71.5	-	-
Claude 3.5 Sonnet	✅	78.3	16.0	65.0	65.3	66.4
GPT-4o	✅	74.6	9.3	49.9	63.8	69.1
Kimi k1.5	✅	96.2	77.5	-	74.9	70.0
Qwen2.5-VL-72B-Instruct	✅	-	-	-	74.8	70.2
LLaVA-Onevision-72B	✅	-	-	-	67.5	56.8
InternVL2-Llama3-76B	✅	-	-	-	65.5	62.7
InternVL2.5-78B	✅	-	-	-	72.3	70.1
Skywork-R1V-38B	✅	94.0	72.0	61.6	67.5	69.0

4. Usage

1. Clone the Repository

git clone https://github.com/SkyworkAI/Skywork-R1V.git
cd skywork-r1v/inference

2. Set Up the Environment

conda create -n r1-v python=3.10
conda activate r1-v
bash setup.sh

3. Run the Inference Script

CUDA_VISIBLE_DEVICES="0,1" python inference_with_transformers.py \
    --model_path path \
    --image_paths image1_path \
    --question "your question"

5. Citation

If you use Skywork-R1V in your research, please cite:

@misc{peng2025skyworkr1vpioneeringmultimodal,
      title={Skywork R1V: Pioneering Multimodal Reasoning with Chain-of-Thought}, 
      author={Yi Peng and Peiyu Wang and Xiaokun Wang and Yichen Wei and Jiangbo Pei and Weijie Qiu and Ai Jian and Yunzhuo Hao and Jiachun Pan and Tianyidan Xie and Li Ge and Rongxian Zhuang and Xuchen Song and Yang Liu and Yahui Zhou},
      year={2025},
      eprint={2504.05599},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2504.05599}, 
}

This project is released under an open-source license.

Skywork/Skywork-R1V-38B