Zhipu AI Unveils First SOTA-Level Native Agent Foundation Model, GLM-4.5

Breaking NewsJul. 29, 2025

Summarized by NextFin AI

Zhipu AI has launched GLM-4.5, the first SOTA-level native agent large model, which is now open-sourced for public use.
GLM-4.5 is ranked first in benchmark evaluations, offering performance comparable to leading models with twice the parameter efficiency.
The model provides API access at one-tenth the price of Anthropic's Claude, with generation speeds exceeding 100 tokens per second.
It uniquely integrates multiple capabilities such as reasoning, coding, and agent functionalities within a single architecture.

AsianFin — Zhipu AI has released and open-sourced its flagship foundation model GLM-4.5, marking the debut of the world’s first SOTA-level native agent large model, according to an official company announcement.

Ranked first in comprehensive benchmark evaluations, GLM-4.5 delivers performance on par with the world’s leading flagship models while boasting twice the parameter efficiency. The model offers API access at just one-tenth the price of Anthropic’s Claude, with generation speeds exceeding 100 tokens per second.

GLM-4.5 is the first model to natively integrate multiple capabilities—including reasoning, coding, and agent-based functionalities—within a single architecture. The model is now available for free public use via Zhipu Qingyan and the z.ai platform.

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Insights

What are the key features of Zhipu AI's GLM-4.5 model?

How does GLM-4.5 compare to other flagship AI models in terms of performance?

What are the advantages of GLM-4.5's parameter efficiency?

What is the significance of integrating multiple capabilities within a single architecture for AI models?

What feedback have users provided about the performance of GLM-4.5?

How does the pricing of GLM-4.5's API access compare to competitors like Anthropic's Claude?

What recent developments have occurred in the AI foundation model landscape?

How has Zhipu AI positioned itself in the current market of AI models?

What challenges does Zhipu AI face in competing with established AI companies?

What potential implications does the release of GLM-4.5 have for the future of AI development?

Are there any notable use cases for GLM-4.5 that highlight its capabilities?

How does GLM-4.5's generation speed impact its usability in real-world applications?

What controversies exist surrounding the use of foundation models like GLM-4.5?

How does the open-sourcing of GLM-4.5 influence the broader AI community?

What historical trends have led to the development of such advanced AI models?

How do different AI models like GLM-4.5 and Claude address similar challenges in performance?

What are the anticipated future trends in the AI foundation model sector?

How might Zhipu AI's advancements influence competition in the AI market?

What role does reasoning play in the functionality of GLM-4.5?

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