The decision marks a departure from standard industry practice, where AI developers typically share pre-release versions of major models with leading chipmakers to ensure optimal performance on widely used hardware.

Instead, DeepSeek granted early access to domestic suppliers, including Huawei Technologies, the sources said. The move gives Chinese chipmakers several weeks to optimise the software for their processors ahead of the model’s expected release.

Nvidia and AMD declined to comment, while DeepSeek and Huawei did not respond to requests for comment.

The reasons behind the decision were not immediately clear. However, industry analysts suggest the move could align with broader Chinese government efforts to reduce reliance on U.S. semiconductor technology.

The development comes amid heightened scrutiny over U.S. export controls. A senior Trump administration official recently told Reuters that DeepSeek’s latest AI model was trained using Nvidia’s most advanced Blackwell chips in mainland China, a potential violation of U.S. export restrictions. U.S. policy currently bars shipments of certain advanced AI chips to China.

DeepSeek’s models have been downloaded more than 75 million times on the open-source platform Hugging Face since the company gained global attention in early 2025. Chinese open-source AI models have seen rapid adoption, surpassing downloads of models from other countries on the platform over the past year.

U.S. authorities previously allowed Nvidia’s H20 and AMD’s MI308 chips, designed for AI inference, to resume shipments to China, though licenses for more advanced processors remain restricted. It is unclear whether DeepSeek has obtained approval to purchase those chips.

Analysts say the immediate commercial impact on Nvidia and AMD may be limited, as DeepSeek’s models primarily serve as benchmarks rather than enterprise deployment standards. However, the decision underscores growing technological and geopolitical tensions as Chinese AI firms prepare to release new models in the coming months.

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The losses — spanning Nvidia, Microsoft, Meta, Broadcom, Oracle, TSMC, AMD, Palantir, Apple and ASML — rattled markets globally, given the companies’ central role in the AI hardware and software supply chain. The sell-off erased an amount nearly equivalent to the entire Spanish stock market and almost half the market capitalisation of Canada.

Nvidia saw the steepest decline, shedding roughly $459 billion, followed by Microsoft ($333 billion) and Meta ($321 billion). Broadcom lost an estimated $173 billion, while Oracle, TSMC, AMD, Palantir, Apple and ASML recorded declines ranging from $21 billion to $102 billion.

The downturn came amid a broader tech-sector slump as investors reassessed whether the nearly two-year surge in AI-linked valuations had overshot fundamentals. Analysts pointed to a series of catalysts behind the sudden reversal. Alphabet’s reported push to supply its home-grown TPUs directly to major customers, including Meta, intensified concerns about rising competition in the AI chip market. Washington’s decision to further tighten export controls on advanced processors bound for China added additional pressure on chipmakers and manufacturing partners.

The sell-off was further fuelled by profit-taking after significant gains, as well as renewed questions about whether massive AI-related capital expenditure will translate into near-term earnings. Some AI software firms, including Palantir, had recently signalled slower-than-expected contract growth, adding to investor unease.

Despite the declines, all ten companies remain among the world’s most valuable corporations, reflecting the continued strategic importance of AI computing infrastructure. The episode underscored, however, how concentrated global equity markets have become; with mega-cap AI stocks now representing an outsized share of major indices, volatility in a handful of companies can move markets worldwide.

Within weeks of the sell-off, Nvidia’s stronger-than-expected quarterly results helped stabilise sentiment, though analysts say the correction served as an early reminder of the risks that accompany rapid technological transitions and elevated valuations in the AI sector.

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