Model Releases
GLM-5: Zhipu AI's Open-Source Reasoning Frontier
Zhipu AI launches GLM-5, China's first public frontier model, optimized for complex engineering and agentic workflows.
February 11, 2026
Model ReleaseGLM-5
Introduction
On February 11, 2026, Zhipu AI officially unveiled GLM-5, marking a significant milestone as China's first public AI company frontier model. This release signals a strategic shift towards domestic capability building and advanced reasoning, moving beyond simple chat interactions to tackle complex systems engineering. As the global AI race intensifies, GLM-5 positions Zhipu as a key player in the domestic market.
Unlike previous iterations that focused primarily on conversational fluency, GLM-5 is architected specifically for long-horizon agentic tasks. This means it can plan, execute, and debug multi-step workflows autonomously. The model represents a convergence of Zhipu's research on language understanding and their new focus on hardware compatibility with domestic chips.
For developers looking to integrate robust reasoning capabilities without relying on proprietary black-box models, GLM-5 offers an open-source alternative. The release coincides with Zhipu's pivot to domestic chip acceleration, ensuring that high-performance inference is possible within China's regulatory and hardware landscape.
- Released: February 11, 2026
- Category: Reasoning Model
- License: Open Source
- Focus: Complex Systems & Agents
Key Features & Architecture
GLM-5 introduces a sophisticated Mixture of Experts (MoE) architecture designed to balance computational efficiency with high reasoning density. The model utilizes a dynamic routing mechanism that activates only the necessary expert networks for specific tasks, reducing latency while maintaining high accuracy on complex logic puzzles.
One of the standout features is the expanded context window, which allows the model to process and retain information across massive datasets. This is crucial for long-horizon tasks where state maintenance over hundreds of steps is required. The architecture also supports native multimodal inputs, enabling visual reasoning alongside text.
The model is optimized for the OpenClaw agent ecosystem, specifically designed to improve how AI systems execute complex automated tasks. This integration ensures that GLM-5 can seamlessly interact with external tools, APIs, and databases, making it a true agentic foundation model rather than just a text generator.
- Architecture: MoE (Mixture of Experts)
- Context Window: 256K Tokens
- Multimodal: Text + Vision
- Optimized for: OpenClaw Ecosystem