{"id":28159,"date":"2025-08-22T15:59:21","date_gmt":"2025-08-22T18:59:21","guid":{"rendered":"https:\/\/nocodestartup.io\/?p=28159"},"modified":"2025-09-02T17:20:44","modified_gmt":"2025-09-02T20:20:44","slug":"model-glm-4-5","status":"publish","type":"post","link":"https:\/\/nocodestartup.io\/en\/model-glm-4-5\/","title":{"rendered":"GLM 4.5: The Revolutionary Language Model for Agents and Complex Reasoning"},"content":{"rendered":"

The advancement of language models has transformed the way we interact with technology, and the GLM 4.5<\/strong> It emerges as an important milestone in this evolution.

Developed by the Zhipu AI team, this model has been gaining global recognition by offering a powerful combination of computational efficiency, structured reasoning, and advanced support for artificial intelligence agents.<\/p>\n\n\n\n

For developers, companies, and AI enthusiasts, understanding what GLM 4.5 is and how it compares to other standards is crucial. LLMs<\/a> It is essential to take full advantage of its features.<\/p>\n\n\n\n

\"What
What is GLM 4.5 and why does it matter?<\/figcaption><\/figure>\n\n\n\n

What is GLM 4.5 and why does it matter?<\/strong><\/h2>\n\n\n\n

O GLM 4.5<\/strong><\/a> It is a Mixture of Experts (MoE) type language model, with 355 billion total parameters and 32 billion active parameters per forward pass.

Its innovative architecture allows for the efficient use of computing resources without sacrificing performance in complex tasks.

The model is also available in lighter versions, such as the GLM 4.5-Air<\/strong><\/a>, optimized for cost-effectiveness.<\/p>\n\n\n\n

Designed with a focus on reasoning tasks, code generation, and interaction with autonomous agents, GLM 4.5 stands out for its support for... hybrid way of thinking<\/strong>, which alternates between quick responses and in-depth reasoning on demand.<\/p>\n\n\n\n

Technical characteristics of the GLM 4.5<\/strong><\/h2>\n\n\n\n

The technical advantage of GLM 4.5 lies in its combination of optimizations to the MoE architecture and improvements to the training pipeline. Among the most relevant aspects are:<\/p>\n\n\n\n

Intelligent and balanced routing<\/strong><\/h3>\n\n\n\n

The model employs sigmoid gates and QK-Norm normalization to optimize routing between specialists, ensuring better stability and utilization of each specialized module.<\/p>\n\n\n\n

Extended context capability<\/strong><\/h3>\n\n\n\n

With support for up to 128,000 entry tokens<\/strong><\/a>, The GLM 4.5 is ideal for long documents, extensive code, and deep conversation histories. It is also capable of generating up to 96,000 output tokens.<\/p>\n\n\n\n

Muon Optimizer and Grouped-Query Attention<\/strong><\/h3>\n\n\n\n

These two advancements allow GLM 4.5 to maintain high computational performance even with the scalability of the model, benefiting both on-premises and cloud deployments.<\/p>\n\n\n\n

\"GLM
GLM 4.5 Tools, APIs, and Integration<\/figcaption><\/figure>\n\n\n\n

GLM 4.5 Tools, APIs, and Integration<\/strong><\/h2>\n\n\n\n

The Zhipu AI ecosystem facilitates access to GLM 4.5 through APIs compatible with the OpenAI standard, as well as SDKs in various languages. The model is also compatible with tools such as:<\/p>\n\n\n\n