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Trump says he didn’t discuss Nvidia’s Blackwell chips with Xi

US President Donald Trump said he did not discuss Nvidia’s Blackwell AI chips with Chinese President Xi Jinping during their recent talks.

He clarified to reporters on Air Force One that while Nvidia’s chip sales to China were mentioned, the conversation did not include the latest Blackwell accelerators.

Trump added that further discussions about Nvidia’s access to the Chinese market are now up to Beijing.

Earlier, he had said he would address the Blackwell chips with Xi, sparking speculation about possible changes to US export policy on advanced semiconductors.

🔗 Source: Bloomberg

🧠 Food for thought

Implications, context, and why it matters.

Blackwell chips stay restricted in China, so Trump’s comments have little practical impact

  • Nvidia’s Blackwell series (B100/B200/B300, its latest AI accelerators) stays under US export controls with no China-ready versions approved for sale 1
  • The US has granted limited, case-by-case licenses to ship the lower-spec H20 to China 1. Chinese regulators then barred buyers from the H20 and the RTX Pro 6000D, while a hypothetical B30A at roughly half a B300 could deliver about 12 to 17x the H20’s compute if licensed 1
  • Trump’s talk of “leaving it to Beijing” holds little practical sway, since any shift needs explicit US action to approve new variants or grant special licenses 2
  • The US keeps its AI compute edge through volume, with about 3.67 million B300-equivalent chips expected in 2025 versus China’s 40,000 to 146,000 B300-equivalents from Huawei 1. “B300-equivalent” means performance normalized to a single Nvidia B300 1

Openings for startups building AI workload migration tools for Chinese developers

  • Many Chinese firms still favor Nvidia hardware despite curbs, which frustrates teams pushed to domestic options like Huawei’s Ascend (Huawei’s line of AI accelerators) 3
  • Huawei’s Ascend 910C hits about 60% of Nvidia H100’s inference speed and runs into software bugs and crashes 45. The H100 is Nvidia’s flagship data center graphics processing unit (GPU) from the prior generation 45
  • A wide gap between Nvidia’s Compute Unified Device Architecture (CUDA) ecosystem and Huawei’s Compute Architecture for Neural Networks (CANN)/MindSpore creates pull for tools that smooth the switch 5
  • Vendors that simplify PyTorch (an open-source AI framework) to Ascend migrations or tune models for weaker hardware can win budget from Chinese AI companies adapting to chip limits 65

Recent Nvidia developments

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