GLM-5.1 (Non-reasoning)

GLM-5.1 (Non-reasoning) is a flagship foundation model developed by Z.ai (formerly Zhipu AI), released as an open-weights model following its spin-out from Tsinghua University. This variant is specifically optimized for high-throughput, direct-output scenarios where extended internal chain-of-thought processing is not required. By operating without the "thinking" mode active in its reasoning-heavy counterpart, it delivers faster response times and lower latency while maintaining elite performance in code generation and complex tool-use scenarios.

The model utilizes a Mixture-of-Experts (MoE) architecture with a total of 754 billion parameters, of which roughly 40 billion are active during any single inference step. A significant technical milestone for GLM-5.1 is its training infrastructure; the model was trained entirely on Huawei Ascend 910B chips using the MindSpore framework, demonstrating the capability to produce frontier-level performance using a completely domestic hardware and software stack.

Key capabilities of GLM-5.1 include advanced software engineering and autonomous agent execution. It famously achieved a score of 58.4 on the SWE-Bench Pro benchmark, outperforming many contemporary closed-source models. The model is designed for long-horizon tasks, supporting autonomous execution loops that can last up to 8 hours, during which it can independently plan, execute code, test, and self-correct to deliver functional software deliverables.

GLM-5.1 supports a 200,000-token context window and features native support for the Model Context Protocol (MCP), function calling, and context caching. Released under the MIT License, the model weights are publicly available for commercial and research use. While it lacks the visual and audio input capabilities of some multimodal variants, it remains a leading choice for text-based engineering, logic, and agentic workflows within the open-source ecosystem.