GLM-4.5 sits as an earlier generation in Z.AI's GLM series of open-weight large language models, built on a Mixture-of-Experts design with 355 billion total parameters and roughly 32 billion active per inference. It was pre-trained on 23 trillion tokens of data, establishing the scaling foundation that Z.AI later extended in its successor releases. The open-weight release positions GLM-4.5 as a flexible base that downstream developers can fine-tune, distill, or deploy for domain-specific reasoning and tool-calling workflows.

Within the broader GLM roadmap, GLM-4.5 represents the stepping-stone generation whose parameter scale and training corpus directly informed the architectural growth seen in later Z.AI models. Its MoE structure allows substantial total capacity while keeping per-token compute manageable, making it a practical option for teams that need strong reasoning behavior without committing to the heaviest inference footprints. Developers working on agentic pipelines, structured outputs, or instruction-tuned derivatives often reference GLM-4.5 as a reliable open baseline before adopting newer GLM variants.