Innovation in artificial intelligence continues at an unprecedented pace, and GLM-4.5 is at the forefront of this evolution. Designed to unify reasoning, coding, and agentic functionalities, GLM-4.5 brings together the most sought-after capabilities in a single, scalable architecture. Whether you are a developer, researcher, or enterprise leader, these models offer new possibilities in building and deploying intelligent applications.
Breakthrough Model Architecture and Features
GLM-4.5’s architecture is engineered for power and flexibility. With 355 billion total parameters (32 billion active), it leverages a Mixture of Experts (MoE) design that emphasizes depth, resulting in superior reasoning capacity. Its streamlined sibling, GLM-4.5-Air, provides a lighter option with 106 billion total (12 billion active) parameters, maintaining high performance for resource-constrained settings.
- Hybrid Reasoning: Seamlessly transitions between complex tool-using and rapid response modes.
- Comprehensive Training: Trained on expansive datasets and refined with advanced reinforcement learning (RL) phases.
- Open Access: Freely available via Z.ai, APIs, HuggingFace, and ModelScope for a range of use cases.
These features empower GLM-4.5 to tackle intricate tasks, support local inference, and remain adaptable to various deployment frameworks.
Performance That Sets New Standards
GLM-4.5 consistently ranks among the top three language models globally, as demonstrated by its results on 12 industry benchmarks. Its agentic task abilities, measured by τ-bench and BFCL-v3, are competitive with the best from OpenAI, Anthropic, and Google DeepMind.
With a 128k token context window and robust function-calling, GLM-4.5 excels at handling complex, multi-step interactions, making it ideal for applications like autonomous web browsing and advanced coding tasks.
- Agentic Tasks: High scores and a 90.6% tool-calling success rate underscore reliability.
- Reasoning: Near state-of-the-art outcomes on MMLU Pro (84.6), AIME24 (91.0), and MATH 500 (98.2), leading in math, science, and logic.
- Coding: Exceptional results on SWE-bench Verified (64.2) and Terminal Bench (37.5), with native support for popular coding frameworks.
Real-World Use Cases and Interactive Demos
GLM-4.5’s practical strengths are highlighted through interactive demos and real-world applications:
- Artifact Generation: Creation of interactive games, simulations, and data visualizations using HTML, SVG, and Python.
- Slides Creation: Automated generation of visually rich presentations, drawing content and images from the web.
- Full Stack Development: End-to-end web app creation with multi-turn dialogues for iterative refinement and deployment.
These capabilities position GLM-4.5 as a creative and technical collaborator for developers, educators, and enterprise teams alike.
Seamless Access and Flexible Deployment
Getting started with GLM-4.5 is straightforward. Users can interact with the model on Z.ai for chat, presentations, and code generation. Integration is simplified through OpenAI-compatible APIs, and open-source model weights support local deployment with frameworks like vLLM and SGLang. Comprehensive guides ensure fast onboarding for both individuals and organizations.
Innovative Training and Infrastructure
The impressive performance of GLM-4.5 is rooted in a rigorous training pipeline:
- Pre-Training: Multi-stage training on diverse, large-scale datasets to build foundational capabilities.
- Reinforcement Learning: Utilizes the open-source slime framework for efficient, scalable RL, especially for agentic tasks.
- Post-Training: Specialized RL methods, including dynamic sampling and adaptive clipping, further enhance reasoning and reliability.
This approach ensures the model adapts to a wide array of complex real-world scenarios, delivering robust, high-quality results.
The Future of Unified Intelligence
GLM-4.5 establishes yet another new benchmark for unified AI by integrating advanced reasoning, coding, and agentic skills within an open-access framework. Its standout performance, versatility, and innovative design make it well-suited for both research and practical deployments, paving the way for the next generation of intelligent, autonomous solutions.
Z.AI GLM-4.5: Redefining Unified AI Reasoning and Coding