GLM 5V Turbo (Reasoning)

GLM 5V Turbo (Reasoning) is a native multimodal large language model developed by Zhipu AI (Z.ai), specifically engineered for agentic workflows and vision-grounded programming. Released as part of the GLM-5 generation, the model is designed to bridge the gap between visual perception and complex logical execution. Unlike models that utilize a separate vision encoder as a post-hoc addition, this model employs a native multimodal fusion approach, processing images, video, and text within a single unified architecture from the pre-training stage.

The model is built on a Mixture of Experts (MoE) architecture featuring 744 billion total parameters, with 40 billion active per token. It incorporates a proprietary CogViT vision encoder for high-fidelity spatial awareness and an inference-friendly Multi-Token Prediction (MTP) architecture. These technical choices enable the model to maintain high performance in long-horizon reasoning tasks, particularly those involving the generation of extensive codebases or the navigation of complex graphical user interfaces (GUIs).

Key capabilities of GLM 5V Turbo include a dedicated Reasoning (Thinking) Mode, which allows the model to perform internal chain-of-thought processing before delivering a final response. This is especially effective in "design-to-code" scenarios where the model converts UI mockups into functional frontend code, and in agentic environments where it must plan and execute multi-step actions. The model supports video analysis for debugging and temporal understanding, as well as native visual grounding to identify precise coordinates within an interface.

Optimized for high-throughput and long-context scenarios, the model features a context window of approximately 202,752 tokens. It is frequently integrated into agent frameworks such as OpenClaw and Claude Code to handle tasks ranging from automated repository exploration to real-world GUI interaction on Android and web platforms.