GLM-5

GLM-5 is an open-source, large-scale MoE (Mixture of Experts) language model designed for complex, long-horizon agentic tasks and systems engineering. With 744 billion parameters and 40 billion actively engaged, it pushes the boundaries of AI capabilities, making it suitable for advanced research and development in AI-driven automation, decision-making, and system modeling. Its architecture features DeepSeek Sparse Attention, which enhances efficiency in processing extensive sequences, and an innovative 'slime' reinforcement learning infrastructure, enabling more adaptable and goal-oriented AI behavior. As the top open-source contender on Vending Bench 2, GLM-5 is narrowing the gap with proprietary models like Claude Opus 4.5, making it a compelling choice for organizations seeking transparency and customization in their AI solutions. Its focus on agentic and complex system tasks positions it as a versatile tool for developers and researchers aiming to push AI frontiers.