This technical report published on February 17, 2026 introduces GLM-5, a next-generation flagship language model developed to master agentic tasks, complex coding, and autonomous reasoning. To achieve state-of-the-art efficiency, the architecture utilizes a Mixture-of-Experts (MoE) framework combined with DeepSeek Sparse Attention and specialized Multi-token Prediction. The model excels at end-to-end software engineering, demonstrating superior performance on benchmarks like SWE-bench and LMArena by employing advanced "thinking" modes. Training was optimized through a fully asynchronous reinforcement learning infrastructure and a hybrid reward system that balances rule-based accuracy with human-like emotional intelligence. Additionally, GLM-5 features full-stack adaptation for various Chinese GPU ecosystems, ensuring high-performance deployment across diverse hardware platforms. This release marks a significant step toward Artificial General Intelligence by transforming models from passive repositories into active, efficient problem solvers. Source: February 17, 2026 GLM-5: from Vibe Coding to Agentic Engineering Zhipu AI & Tsinghua University GLM-5 Team https://arxiv.org/pdf/2602.15763