Qwen2.5-VL-32B
Qwen2.5-VL-32B is an open source 32B parameter multimodal AI model that supports image understanding, mathematical reasoning, text generation and visual Q&A
English
English
Qwen2.5-VL-32B is an open source 32B parameter multimodal AI model based on the Qwen2.5-VL series. After reinforcement learning optimization, it has more in line with human preference answering style, strong mathematical reasoning ability, and more refined image understanding and reasoning ability. The model performs well in multimodal tasks (such as MMMU, MMMU-Pro, MathVista) and plain text tasks, and even surpasses the Qwen2-VL-72B model.
Image understanding and description : parse images, identify objects and scenes, and generate detailed natural language descriptions.
Mathematical reasoning and logical analysis : Solve complex mathematical problems and perform multi-step reasoning.
Text generation and dialogue : Generate natural language answers based on input text or images, supporting multiple rounds of dialogue.
Visual Q&A : Answer image-related questions and support complex visual reasoning.
Multimodal pre-training : Pre-training using image and text data to achieve cross-modal understanding and generation.
Transformer architecture : Adopt self-attention mechanism to improve understanding and generation accuracy.
Reinforcement learning optimization : Optimize model output, which is more in line with human preferences.
Visual Language Alignment : Ensure semantic alignment of image and text features through contrast learning.
Better than the same-scale models, such as Mistral-Small-3.1-24B and Gemma-3-27B-IT, surpassing Qwen2-VL-72B-Instruct.
Excellent in multimodal tasks such as MMMU, MMMU-Pro, and MathVista.
Show the best performance in the same-scale model in plain text tasks.
Intelligent customer service : Improve customer service efficiency and accurately answer image and text questions.
Educational assistance : Answer math questions and help students understand learning materials.
Image annotation : Automatically generate image descriptions to enhance content management capabilities.
Intelligent driving : analyze traffic information and provide driving advice.
Content creation : Generate text based on images to assist in video and advertising creation.
Project official website : Qwen2.5-VL-32B official website
HuggingFace Model Library : Qwen2.5-VL-32B HuggingFac
