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DeepSeek Delays R2 After Training Failures on Huawei Chips, Resumes on Nvidia H20

Beijing's push for homegrown AI accelerators is running into tooling gaps that keep Nvidia GPUs central to large-model training.

The logo of Nvidia Corporation is seen during the annual Computex computer exhibition in Taipei, Taiwan May 30, 2017. REUTERS/Tyrone Siu/File Photo
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Overview

  • Multiple reports say DeepSeek could not complete a single R2 training run on Huawei’s Ascend 910C chips despite on-site help from Huawei engineers.
  • The company has resumed training on Nvidia H20 GPUs after U.S. licensing allowed H20 sales to China, while retaining Ascend hardware for inference.
  • R2, initially slated for May 2025, was postponed as DeepSeek grappled with Ascend-related stability and software issues and expanded data labeling for the new dataset.
  • Reports from SCMP indicate state-funded AI data centers in China must source more than 50% of chips from domestic vendors, creating friction because CUDA-trained models do not cleanly port to Huawei’s CANN stack.
  • Operators cite persistent gaps in stability, interconnect performance and software maturity versus Nvidia’s ecosystem, even as firms such as Cambricon plan to raise about 4 billion yuan to capture mandated demand.