Z.ai

GLM-5-Turbo is a lightweight, low-latency variant of the GLM-5 family designed for high-throughput chat and application workloads. Optimized for cost-efficient inference, enabling large-scale deployments like assistants, agents, and real-time apps. Supports long-context conversations and structured tool use, making it suitable for agent pipelines and coding workflows. Provides strong multilingual performance, particularly for Chinese and English usage scenarios. Available through the Z.ai API ecosystem, targeting developers building production LLM applications.

Repositioned as the new flagship for “agentic engineering,” targeting longer-horizon agent tasks end to end. Introduces a dedicated programming-enhanced variant (“GLM-5-Code”) for more stable tool-invoking coding agents. Stronger front-end generation accuracy called out explicitly for pages, animations, minigames, and 3D outputs. Coding and agent performance is claimed as open-source SOTA, with usability approaching Claude Opus 4.5. Keeps the same 200K context baseline while shifting the focus to higher reliability on long-range execution.

More stable multi-step reasoning and execution, tuned for “task completion” workflows. Bigger jump in agentic coding and terminal-based tasks (reported benchmark gains on SWE-bench and Terminal Bench). Stronger tool invocation, with higher reported scores on web browsing and interactive tool benchmarks. Better front-end aesthetics and UI generation quality by default (webpages, slides, posters). Added improvements to reasoning-control methods (retained and round-based reasoning) for more controllable complex runs.

Context window increased from 128K to 200K for heavier agent tasks. Over 30% better token efficiency in real-world coding tests. Stronger coding performance, including better results in common coding-agent environments. Better reasoning plus explicit tool use during inference for stronger overall capability. More capable tool and search agents, with tighter integration into agent frameworks.