glm-4v

GLM-4V is a flagship multimodal model launched by Zhipu AI. Its core positioning is as a vision-understanding engine based on the MOE architecture, featuring 1120×1120 high-resolution input and a deep-thinking mode to achieve precise analysis of images, videos, and documents, as well as cross-modal task processing.

• Multimodal Fusion: Supports three types of inputs—images, videos, and files—and delivers accurate text-analysis results, covering enterprise-level scenarios such as front-end replication and security quality inspection.
• High-Resolution Processing: Exclusively supports 1120×1120 resolution input; uses downsampling technology to reduce token overhead and enhance parsing accuracy.
• Performance on Par with GPT-4V: Outperforms comparable open-source models in multiple evaluations, achieving SOTA-level overall performance, especially excelling in complex visual reasoning tasks.
• Structured Output: Natively supports JSON format, enabling direct integration with business systems and reducing secondary development efforts.
• Enterprise-Level Customization: Supports LoRA fine-tuning, increasing model availability from 60% to 89%.
• Open-Source Ecosystem: The open-source version has been downloaded over 13 million times, ranking first among domestically developed models, and supports developers in deploying lightweight applications locally.

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Core Capabilities

🧠 MOE Architecture Powered: With a total parameter count of 10.6B and 1.2B activated parameters, it achieves the highest performance among comparable open-source models, boosting visual reasoning efficiency by 40%.

🔍 Full-Modal Analysis: Exclusively supports three modalities—video, image, and file—as input, enabling multi-source information fusion analysis in a single call.

⚡ Deep-Thinking Mode: Dynamically activates complex reasoning chains to tackle advanced tasks such as subject-specific problem-solving and logical deduction, with an accuracy rate exceeding 92%.

🌐 High-Resolution Processing: With 1120×1120 input resolution and intelligent downsampling, detail-capturing capability improves by 50%, minimizing information loss.

🛠️ Automated Execution: A GUI Agent precisely identifies interface elements and automatically performs office operations such as PPT editing and data entry.

📊 Structured Output: Natively supports JSON format and coordinate-based localization (such as Grounding), directly generating interactive code or structured data.