In the latest released GLM-5.1, this open-source model demonstrates its exceptional intelligence level, capable of working independently for up to 8 hours and completing complex engineering projects. Compared to previous models that could only interact for short periods, GLM-5.1 shows significant improvements in code capabilities and long-term task execution.
The model performs outstandingly among global open-source models, achieving excellent results on multiple code evaluation benchmarks. In the SWE-Bench Pro benchmark test, GLM-5.1 successfully located and fixed high-level engineering bugs, surpassing existing top models such as GPT-5.4 and Claude Opus4.6. This marks its strong capability in the field of professional software development.
The way GLM-5.1 works is astonishing. It can build a complete Linux desktop system at night, taking 8 hours and executing over 1200 steps. It delivered preliminary results within 20 minutes. The final delivered system is fully functional, equivalent to the work of four developers for a week. Additionally, it also shows remarkable performance in vector database optimization and self-evolution under real machine learning loads, demonstrating the potential of AI in engineering fields.
The biggest highlight of this model is its ability to self-assess and optimize. When facing complex tasks, GLM-5.1 not only identifies and solves problems but also actively adjusts strategies to achieve optimal results. This capability provides a new direction for the development of AI in practical applications.
The release of GLM-5.1 marks the beginning of a new technological era. Developers only need to give instructions and can expect it to work efficiently over long periods.
- GitHub:https://github.com/zai-org/GLM-5
- Hugging Face:https://huggingface.co/zai-org/GLM-5.1
- ModelScope:https://modelscope.cn/models/ZhipuAI/GLM-5.1
Key Points:
🌟 GLM-5.1 can independently complete complex tasks for 8 hours, improving code capabilities.
💻 Performs exceptionally well on multiple code evaluation benchmarks, surpassing many top models.
🔧 Has self-assessment and optimization capabilities, showcasing the wide application potential of AI in engineering fields.
