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DeepSeek partners with Huawei to develop chip programming tools, reducing reliance on Nvidia

DeepSeek said on Wednesday it has partnered with Huawei Technologies to develop and open-source programming infrastructure for Huawei's Ascend chips, including compute and communication libraries, as Chinese AI firms seek alternatives to Nvidia's ecosystem. The two companies jointly advanced a "supernode" solution based on 128 Ascend 950 chips, and DeepSeek highlighted TileLang, a high-level open-source programming language for AI chips, as offering "a simpler programming model" than Nvidia's CUDA. The announcement came two weeks after Huawei unveiled its next generation of AI processors and supernode computing systems.

by read1 min views1 publishedSep 30, 2026
DeepSeek partners with Huawei to develop chip programming tools, reducing reliance on Nvidia
Image: Ca (auto-discovered)

By Che Pan and Farah Master

BEIJING/HONG KONG, Sept 30 (Reuters) - Chinese AI firm DeepSeek said on Wednesday it has partnered with Huawei Technologies to develop programming tools optimised for Huawei's Ascend chips, the latest sign of Chinese tech firms deepening ties as they seek alternatives to the Nvidia ecosystem.

In a post on its official WeChat account, DeepSeek said it was open-sourcing programming infrastructure for Huawei's Ascend platform, including compute and communication libraries.

The announcement came two weeks after Huawei unveiled its next generation of AI processors and supernode computing systems, and said it expected its AI systems to be widely used for model training next year.

DeepSeek said Huawei provided full support in developing the programming infrastructure, and the two companies jointly advanced a "supernode" solution based on 128 Ascend 950 chips, optimising both computation and communication.

DeepSeek also highlighted the role of TileLang, a high-level open-source programming language for AI chips, in improving development efficiency and simplifying code logic.

"To build a new generation of independent, self-controlled GPU software ecosystems, the first priority is establishing a high-level language that is universal, easy to program, and still capable of reaching the hardware's full performance potential," DeepSeek said.

"TileLang was created precisely to meet this need," and offers "a simpler programming model" than Nvidia's CUDA, DeepSeek said.

(Reporting by Che Pan and Farah Master; Editing by Tom Hogue and Kevin Buckland)

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