哈萨克斯坦扩大 AI 算力部署
Kazakhstan Expands Compute for Its AI Future
Firebird 获准在哈萨克斯坦部署 45,000 块 NVIDIA Grace Blackwell GPU，Kazakhtelecom 已部署 400 块 H200 和 480 块 B300 GPU。Firebird 计划建设总容量约 500 兆瓦的 AI 基础设施，并设立 Firebird Labs 支持本地初创企业。这标志着哈萨克斯坦 AI 生态正从基础设施规划转向实际部署阶段。
Kazakhstan’s AI ecosystem is moving from infrastructure plans to deployment.
The shift is visible across the full AI stack — from infrastructure to models to applications.
Together, the ecosystem announcements below point to the nation’s increasing supply of accelerated computing — along with its growing demand for what comes next.
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The Infrastructure Layer Is Scaling
Building on its first AI factory in Armenia, Firebird is expanding into Kazakhstan, where it has secured a U.S. export license for 45,000 NVIDIA Grace Blackwell GPUs. The first phase is under construction with Kazakhtelecom at Data Center Valley, targeting commercial launch in the third quarter of 2027.
A planned second phase would bring Firebird’s total potential AI infrastructure capacity in Kazakhstan to approximately 500 megawatts. Firebird also plans to establish Firebird Labs Kazakhstan to support local AI startups, research and talent development through funding, access to compute and research partnerships.
Kazakhtelecom, the nation’s largest telecommunications company, has already deployed 400 NVIDIA H200 and 480 NVIDIA B300 GPUs in Astana and Almaty.
Next year, the company plans to deploy more than 1,000 GPUs in the Data Center Valley, along with more than 1,000 NVIDIA Vera Rubin GPUs in the Ekibastuz region, serving diverse workloads with infrastructure that enterprises, developers and institutions can use at scale.
AI-Native Companies Scale With Compute
The nation’s AI-native companies are also building out their compute capacity — and the applications that run atop them.
More local capacity gives developers and companies room to train, fine-tune and serve increasingly capable models. Successful applications, in turn, create demand for more compute.
Kazakhstan’s AI opportunity isn’t defined by GPU counts alone. Connecting that infrastructure with developers, universities, startups and industries can turn accelerated computing into useful applications.
Today’s announcements represent different layers of that stack — infrastructure deployment, access to compute and AI-native product development — where the AI foundation is reaching new scale.
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来源：NVIDIA Blog · blogs.nvidia.com