Core Insights - The article discusses the launch of GLM-5, a next-generation foundational model aimed at shifting programming paradigms from "VibeCoding" to "AgenticEngineering" [1] Group 1: Model Innovations - GLM-5 builds on the intelligence, reasoning, and programming capabilities of its predecessor, GLM-4.5, while employing sparse attention to significantly reduce inference costs [1] - The model maintains long-context capabilities without loss, enhancing its overall performance [1] Group 2: Learning Infrastructure - A new asynchronous reinforcement learning infrastructure has been developed to better align the model with various tasks, decoupling the generation process from the training process to greatly improve post-training iteration efficiency [1] - The introduction of a novel asynchronous Agent reinforcement learning algorithm further enhances the effectiveness of reinforcement learning, allowing the model to learn more effectively from complex, long-range interactions [1] Group 3: Performance Metrics - GLM-5 achieves state-of-the-art (SOTA) performance in mainstream open benchmark tests [1] - The model demonstrates unprecedented capabilities in real-world programming tasks, surpassing all previous open-source baselines in handling end-to-end software engineering challenges [1]
智谱发布GLM-5技术报告，技术细节全公开