哈萨克斯坦扩充算力，布局 AI 未来
Kazakhstan Expands Compute for Its AI Future
哈萨克斯坦正扩大 AI 算力部署，Firebird 已获准向当地出口 45,000 块 NVIDIA Grace Blackwell GPU。其与 Kazakhtelecom 合作的一期项目正在建设，目标于 2027 年第三季度商用。Kazakhtelecom 已在阿斯塔纳和阿拉木图部署 400 块 NVIDIA H200 和 480 块 NVIDIA B300 GPU。
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