GLM-5: from Vibe Coding to Agentic Engineering

Understand

We present GLM-5, a next-generation foundation model designed to transition the paradigm of vibe coding to agentic engineering.

• Building upon the agentic, reasoning, and coding (ARC) capabilities of its predecessor, GLM-5 adopts DSA to significantly reduce training and inference costs while maintaining long-context fidelity.
• To advance model alignment and autonomy, we implement a new asynchronous reinforcement learning infrastructure that drastically improves post-training efficiency by decoupling generation from training.
• Furthermore, we propose novel asynchronous agent RL algorithms that further improve RL quality, enabling the model to learn from complex, long-horizon interactions more effectively.