qwen3-vl-235b-a22b-instruct

Qwen3-VL-235B-A22B-Instruct is a super-large-scale multimodal instruction-tuned model released by Alibaba’s Tongyi Lab, primarily positioned as the “most powerful open-source visual-language intelligence foundation model,” specifically designed for complex image-and-text understanding and tool-collaboration scenarios.

• Flagship MoE Architecture: With a total of 235 billion parameters, it activates only 22 billion parameters, striking a balance between cutting-edge multimodal capabilities and efficient inference costs.
• Natively Supports Long Videos and Documents: It can handle various types of inputs, including images, videos, PDFs, web page screenshots, and more, supporting ultra-long context fusion and analysis in a single inference.
• Comprehensively Enhanced Agent Capabilities: It leads in tasks such as GUI operations, frontend code generation, and chart-based question answering, and supports Function Calling and structured output.
• Built-in Deep Thinking Mode: It can automatically enable Chain-of-Thought reasoning, breaking down complex visual tasks into step-by-step subtasks and solving them sequentially.

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Core Capabilities

👁️ Pixel-Level Semantic Understanding: Accurately identifies interface elements, chart data, document layouts, and correlates them with text instructions for high-level reasoning.

🧠 Autonomous Task Planning: When faced with tasks such as “writing e-commerce detail pages based on product images” or “generating analytical reports from financial statement screenshots,” it can automatically plan the process of parsing → extraction → generation.

🌍 Multi-Language Image and Text Generation: It supports image description, interpretation, and creation in multiple languages including Chinese and English, producing outputs that are culturally appropriate and contextually relevant.

🧩 Seamless Agent Collaboration: Natively compatible with tool-call protocols, it can directly drive browsers, code executors, or design software to build end-to-end automated workflows.