Qwen-VL is a series of open-source large vision-language models (LVLMs) that combine advanced capabilities with accessibility, positioning themselves as a strong competitor to established models like OpenAI's GPT-4V and Google's Gemini. Built on Alibaba Cloud's Qwen-7B model, Qwen-VL integrates a visual receptor architecture to process visual inputs, enabling tasks such as image recognition, captioning, and visual grounding with high accuracy and efficiency. It supports multiple languages, including English and Chinese, and demonstrates superior performance on various vision-language benchmarks, particularly in Chinese text comprehension. Qwen-VL's capabilities include fine-grained visual understanding, visual reasoning, and text information processing, making it effective in real-world applications. The Qwen-VL-Chat variant excels in handling complex multimodal interactions, outperforming other models in benchmarks like the TouchStone and MME. Future plans for Qwen-VL include expanding to more modalities, increasing model size, and enhancing multi-modal generation capabilities to further advance multimodal AI research.