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GLM-5.1 is a next-generation large language model developed by Z.ai for advanced coding, reasoning, and long-horizon agentic engineering tasks. Built as the successor to GLM-5, the model significantly improves performance in software engineering benchmarks, repository generation, and real-world terminal-based workflows. GLM-5.1 is designed to remain effective over extended problem-solving sessions, allowing it to iteratively refine strategies, analyze failures, and sustain productivity across hundreds of reasoning cycles and tool calls. The model leverages large-scale pretraining, reinforcement learning infrastructure, and sparse attention mechanisms to improve efficiency while maintaining strong long-context understanding. It supports deployment through frameworks such as vLLM, SGLang, xLLM, and KTransformers, enabling scalable local inference for enterprise and research use cases.
Features
- Delivers state-of-the-art performance on coding and agentic engineering benchmarks like SWE-Bench Pro and Terminal-Bench 2.0.
- Designed for long-horizon reasoning with sustained optimization across extended multi-step workflows.
- Uses sparse attention and reinforcement learning infrastructure to improve efficiency and scalability.
- Supports local deployment through frameworks including vLLM, SGLang, xLLM, and KTransformers.
- Handles complex coding, repository generation, and terminal-based problem-solving tasks with advanced tool usage capabilities.
- Available in multiple precision formats, including BF16 and FP8, for flexible deployment and performance optimization.
Project Samples
