glm-4.1v-thinking-flash

GLM-4.1V-Thinking-Flash is a free visual reasoning large model launched by Zhipu AI. Its core positioning is a high-performance multimodal foundation that combines powerful visual perception with deep chain-of-thought reasoning, designed to deliver accurate and interpretable analysis in complex visual scenarios.

• Native Deep Thinking Capability: It comes with a default Chain-of-Thought (CoT) reasoning mechanism, performing deep logical inference before providing answers, significantly enhancing the accuracy of responses in complex and ambiguous scenarios.
• Outstanding Multimodal Understanding: Its core capabilities have reached industry-leading levels (new SOTA) in scenarios such as chart analysis, video understanding, and GUI tasks, enabling it to precisely capture subtle logic in images and videos.
• All-Round Visual Analysis: It supports multiple input formats including images, videos, and files, and features temporal analysis and event logic modeling capabilities, allowing it to handle long-term video content.
• Visual Anchoring and Localization: It achieves precise alignment between language instructions and image regions, enabling it to identify and locate specific entities within images, thereby improving the controllability and assistive capabilities of human-computer interaction.

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Core Capabilities

👁️ Deep Integrated Analysis of Text and Images: It not only recognizes text and objects but also understands chart trends, financial statement logic, and complex academic illustrations.

🧠 Step-by-Step Deduction of Complex Logic: For mathematical, physical, and chemical problems or scientific derivations, it provides detailed thinking processes, ensuring rigorous and transparent reasoning paths.

💻 Frontend Coding and GUI Tasks: It boasts exceptional code conversion capabilities, enabling it to directly generate frontend code such as React based on UI screenshots, or act as an agent to understand interface structures and perform automated tasks.

🎬 Temporal Video Understanding: It can analyze action sequences, causal relationships, and logical evolution in videos, making it suitable for applications like surveillance summarization and video question answering.

🔍 Entity-Level Visual Alignment: It excels in “visual localization” tasks, accurately identifying the function of specific parts or regions within images, and is widely used in industrial inspection and smart home interactions.