qwen2-vl-72b-instruct

Qwen2-VL-72B-Instruct is a high-performance multimodal instruction-tuned model released by Alibaba’s Tongyi Lab. Its core positioning is as a flagship multimodal foundation model that delivers powerful visual-language understanding combined with professional-grade text-and-image interaction.

• Ultra-large-scale dense architecture: With 72 billion parameters fully activated, it achieves state-of-the-art performance among open-source models in authoritative multimodal benchmarks such as MMMU, MathVista, and DocVQA.
• Natively supports multimodal inputs: It can directly process complex visual content including images, videos, PDFs, web page screenshots, and more, while seamlessly integrating with long-form text.
• Long-duration video understanding: It can analyze videos longer than 20 minutes, enabling tasks such as video question answering, content creation, and conversational interactions.
• Fine-grained alignment with instructions: Trained on high-quality human preference data, it precisely responds to complex instructions involving format control, style imitation, multi-step operations, and more.

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Core Capabilities

👁️ Expert-level visual parsing: Accurately understands highly information-dense content such as academic charts, engineering drawings, financial reports, and UI interfaces, and extracts structured data from them.

🧠 Cross-modal deep reasoning: Combines visual and textual contexts to accomplish tasks like “writing debugging steps based on circuit diagrams” or “generating shopping recommendations from product comparison images.”

🌍 Natural multilingual output: Strongly enhances Chinese context understanding while supporting mainstream languages such as English, ensuring outputs are aligned with local cultural norms and professional conventions.

🧩 Agent-ready integration: Natively supports Function Calling and JSON Schema output, allowing seamless integration into AI workflows for automated office applications, AI tutoring, e-commerce shopping guides, and more.