GLM-4.5 by Zhipu AI is a high-capacity text-to-text language model featuring a massive 128,000-token context window.
Zhipu AI's GLM-4.5 is a versatile text-to-text large language model designed for diverse natural language processing tasks. Featuring a 128,000-token context window, it supports understanding and generating very long-form text with high coherence and contextual awareness.
GLM-4.5 aims to close the gap by integrating diverse capabilities within a single framework. Across 12 benchmarks spanning agentic tasks (3), reasoning (7), and coding (2), GLM-4.5 achieves an overall third-place ranking. Its variant, GLM-4.5 Air, ranks sixth, showing competitive yet slightly lower results compared to top models from OpenAI, Anthropic, Google DeepMind, xAI, Alibaba, Moonshot, and DeepSeek.
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Vs. Claude 4 Sonnet: GLM-4.5 shows close performance in agentic coding and reasoning tasks but still has optimization potential compared to Claude Sonnet 4, which achieves excellent coding success and state-of-the-art reasoning outputs, often favored for autonomous multi-feature app development.
Vs. OpenAI GPT-4.5: GLM-4.5 ranks overall competitive with top models including GPT-4.5 in reasoning and agent benchmarks, though GPT-4.5 generally leads in raw task accuracy on some professional benchmarks like MMLU and AIME.
Vs. Qwen3-Coder and Kimi K2: GLM-4.5 dominates Qwen3-Coder with an 80.8% success rate and wins 53.9% of tasks against Kimi K2, highlighting its superior coding and agentic capabilities for complex programming scenarios.
Vs. Gemini 2.5 Pro: GLM-4.5 holds its ground on reasoning and coding benchmarks but detailed exact percentages are less public; Gemini 2.5 stands stronger in certain coding and reasoning tests but GLM-4.5 balances large context and agentic tools well.
The full GLM-4.5 model requires substantial computational resources and GPU memory, potentially limiting deployment feasibility for organizations with constrained infrastructure. The lighter GLM-4.5 Air variant addresses this but with fewer active parameters and slightly reduced capabilities.
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