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Native multimodal GLM model for efficient coding and long-horizon agent tasks

原生多模态 GLM 模型，面向高效编程与长程智能体任务

原生多模态 GLM 模型，面向高效编程与长程智能体任务

原生多模态 GLM 模型，面向高效编程与长程智能体任务

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GLM 模型；统一调度池

GLM-5.3-Flash is the first open-source, native multimodal model in the GLM-5 series. It employs a hybrid sparse and linear computation architecture with 320 billion total parameters—of which only 18 billion are active—significantly reducing computational load and cache usage. The model supports visual coding, enabling continuous optimization through the synergy of code and interface interactions; it can also autonomously decompose tasks and invoke tools to efficiently deliver high-quality professional outputs such as PPTX and PDF files.

GLM-5.3-Flash is the first open-source, native multimodal model in the GLM-5 series. It employs a hybrid sparse and linear computation architecture with 320 billion total parameters—of which only 18 billion are active—significantly reducing computational load and cache usage. The model supports visual coding, enabling continuous optimization through the synergy of code and interface interactions; it can also autonomously decompose tasks and invoke tools to efficiently deliver high-quality professional outputs such as PPTX and PDF files.