GLM-5, developed by zai-org, is a large language model with 744 billion parameters (40 billion active) trained on 28.5 trillion tokens, designed for complex systems engineering and long-horizon agentic tasks. It integrates DeepSeek Sparse Attention (DSA) for reduced deployment cost and improved long-context capacity. The model excels in reasoning, coding, and agentic benchmarks, achieving best-in-class performance among open-source models by leveraging a novel asynchronous RL infrastructure called slime for efficient post-training.
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GLM-5: Advanced Agentic AI for Complex Systems
GLM-5, developed by zai-org, is a powerful large language model specifically engineered for complex systems engineering and long-horizon agentic tasks. It represents a significant scale-up from its predecessor, GLM-4.5, featuring 744 billion parameters (40 billion active) and trained on an extensive 28.5 trillion tokens.
Key Capabilities
- Enhanced Agentic Performance: Designed to excel in multi-step, long-horizon tasks, making it suitable for autonomous agents.
- Efficient Long Context: Integrates DeepSeek Sparse Attention (DSA) to maintain long-context capacity while substantially reducing deployment costs.
- Advanced Post-training: Utilizes
slime, a novel asynchronous RL infrastructure, for highly efficient and fine-grained post-training iterations, bridging the gap between pre-trained competence and specialized excellence. - Best-in-Class Benchmarks: Achieves leading performance among open-source models across a wide array of academic benchmarks, particularly in reasoning, coding, and agentic tasks, closing the performance gap with frontier models.
Good for
- Developing AI Agents: Ideal for building sophisticated AI agents that require long-term planning and execution.
- Complex Problem Solving: Excels in tasks demanding advanced reasoning and problem-solving capabilities.
- Code Generation and Debugging: Demonstrates strong performance in coding benchmarks, making it suitable for software development assistance.
- Resource-Efficient Deployment: The integration of DSA allows for more cost-effective deployment while retaining high performance.