What To Know
- In fact, midway through early developer evaluations, this AI Platforms, Models and Apps news report observed that GLM-5 showed a remarkable capacity to function more like an autonomous engineer than a traditional chatbot, signaling a profound transformation in artificial intelligence capabilities.
- 5 trillion tokens, allowing it to understand and reason across a wide range of domains, from programming and research to business and technical problem-solving.
AI Platforms, Models and Apps: The artificial intelligence race has taken a dramatic turn with the launch of GLM-5, a powerful new open-weights model developed by Zhipu AI. Released on February 11, 2026, just days before the Lunar New Year, GLM-5 represents a major leap forward in how AI systems operate. Instead of simply answering questions or generating code snippets, this model is designed to plan, build, and execute complete systems autonomously. This marks a fundamental shift in AI development, moving from passive tools toward active digital engineers capable of handling complex real-world workflows.
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At its core, GLM-5 introduces what experts call “agentic engineering,” a concept where AI models no longer just assist programmers but independently carry out multi-step tasks over extended periods. This means GLM-5 can build software applications, manage business simulations, and coordinate tools without constant human intervention. In practical tests, it demonstrated an ability to maintain goals, allocate resources, and execute long-term strategies across hundreds of steps. In fact, midway through early developer evaluations, this AI Platforms, Models and Apps news report observed that GLM-5 showed a remarkable capacity to function more like an autonomous engineer than a traditional chatbot, signaling a profound transformation in artificial intelligence capabilities.
Massive Scale and New Architecture Drive Performance
GLM-5’s impressive capabilities stem from its massive technical scale and advanced architecture. The model contains approximately 744 billion parameters, more than double its predecessor GLM-4.5, with 40 billion active parameters used dynamically during processing. It was trained on an enormous dataset of 28.5 trillion tokens, allowing it to understand and reason across a wide range of domains, from programming and research to business and technical problem-solving.
One of its most significant innovations is the integration of sparse attention technology originally pioneered by DeepSeek. This technique dramatically improves efficiency by allowing the AI to focus only on the most relevant information within large datasets. As a result, GLM-5 supports a massive 200,000-token context window, enabling it to analyze entire academic papers, generate full-length reports, and manage long conversations without losing track of earlier details.
Another breakthrough lies in its asynchronous reinforcement learning framework, known internally as Slime. This system allows GLM-5 to continuously refine its performance after deployment, improving efficiency and reducing operational costs over time. Combined with its mixture-of-experts design, this enables the model to maintain high performance while controlling resource consumption.
Benchmark Results Show Exceptional Engineering Ability
Performance benchmarks reveal that GLM-5 ranks among the strongest open-source AI models ever released. On SWE-bench-Verified, a widely respected test measuring real-world software engineering ability, GLM-5 scored an impressive 77.8 percent, surpassing many competing open models. It also achieved strong scores on Terminal Bench 2.0 and BrowseComp, demonstrating advanced reasoning and system-level planning abilities.
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One particularly striking demonstration involved a simulated vending machine business. In this year-long test, GLM-5 successfully managed inventory, pricing, and operations, finishing with a profit balance of $4,432. This simulation required strategic planning, resource management, and long-term decision-making—skills traditionally considered beyond the reach of AI models.
The model also showed improved reliability in avoiding hallucinations, meaning it is better at recognizing when it lacks sufficient information rather than generating incorrect answers. This improvement significantly enhances trustworthiness for professional and enterprise applications.
Built on Domestic Hardware and Expanding AI Independence
In addition to its technical advances, GLM-5 represents a milestone in hardware independence. The model was trained entirely on Huawei Ascend processors using China’s domestic computing ecosystem, rather than relying on US-manufactured GPUs. This achievement highlights the growing capability of regional AI infrastructure and reduces reliance on foreign semiconductor supply chains.
GLM-5 is available under an open-weights license, allowing developers worldwide to study and build upon its architecture. However, due to its enormous size and computational demands, most users access the model through cloud-based APIs rather than running it locally.
Competitive Landscape Intensifies in Global AI Race
The release of GLM-5 comes at a time of intense competition among global AI developers. Companies are racing to build models that can go beyond conversation and actively execute tasks. GLM-5’s ability to browse tools, generate complex codebases, analyze long documents, and manage workflows places it firmly at the forefront of this emerging generation of AI systems.
However, the model is not without limitations. It currently operates as a text-only system and lacks multimodal capabilities such as image and video understanding. Some early testers also noted that while GLM-5 excels at execution and planning, its collaborative reasoning style still trails behind some proprietary models.
The Future of AI Is Moving Toward Autonomous Builders
GLM-5’s release signals that artificial intelligence is entering a new phase where machines can act not only as assistants but as independent builders and operators. Its ability to carry out long-term planning, execute complex workflows, and improve continuously after deployment represents a clear shift in AI’s role in software development, research, and business automation.
As open-weights models like GLM-5 become more powerful and accessible, they are expected to accelerate innovation across industries worldwide. Developers, startups, and enterprises may soon rely on AI not just to generate ideas, but to execute them from start to finish. While challenges remain, including infrastructure demands and ongoing reliability improvements, GLM-5 demonstrates that autonomous AI engineering is no longer theoretical—it is becoming a practical reality that will reshape how technology is built and deployed across the global digital economy.
Links:
Model weights: huggingface.co/zai-org/GLM-5
FP8 variant: huggingface.co/zai-org/GLM-5-FP8
API: chat.z.ai
OpenRouter: openrouter.ai/z-ai/glm-5
GitHub: github.com/zai-org/GLM-5
GLM Coding Plan: https://z.ai/subscribe?utm_source=pr&utm_medium=press&utm_campaign=launch
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