The U.S. has approved Nvidia to sell H200 AI chips to roughly 10 Chinese companies—including Alibaba, Tencent, ByteDance, and JD.com—but as of mid‑May 2026 no shipments have occurred because Chinese regulatory approva...

Create a landscape editorial hero image for this Studio Global article: What is the current status of U.S.-approved Nvidia H200 chip sales to Chinese companies, which firms have been cleared and under what licens. Article summary: The H200 China deal is approved on the U.S. side but effectively stalled: about 10 Chinese firms have been cleared to buy Nvidia’s H200 AI chips, yet no deliveries have occurred so far because Chinese-side approvals and . Topic tags: general, general web, user generated, government. Reference image context from search candidates: Reference image 1: visual subject "The US Commerce Department has approved around 10 Chinese companies including Alibaba Group Holding Ltd, Tencent Holdings Ltd, ByteDance Ltd and" source context "US clears chip sales to 10 China firms as Nvidia eyes breakthrough | The Star" Reference image 2: visual subject "Trading ideas: Media, EG,
Nvidia has received U.S. approval to sell its H200 artificial‑intelligence accelerator to several major Chinese technology companies—but the deal remains effectively frozen. Even though export licenses have cleared key buyers, no H200 chips had been delivered to China as of mid‑May 2026, leaving one of the most closely watched semiconductor deals in limbo .
The standoff highlights how AI hardware has become a geopolitical bargaining chip between Washington and Beijing. Both governments are shaping how, when, and whether the transactions can actually occur.
U.S. regulators have approved roughly 10 Chinese companies to purchase Nvidia’s H200 GPUs, the company’s second‑most powerful AI data‑center chip . Despite that approval, shipments have not started.
People familiar with the matter say the absence of deliveries reflects unresolved regulatory and political issues rather than a lack of demand. Chinese cloud and AI firms continue to want the hardware, but cross‑border approvals remain incomplete .
Reporting indicates that several of China’s largest internet and cloud firms are among the approved buyers, including:
These companies are major operators of AI infrastructure and large cloud platforms, making them key potential customers for high‑performance AI accelerators .
The full list of the approximately ten approved companies has not been publicly confirmed, so the named firms represent those identified by sources rather than a complete official roster .
In addition to end customers, the U.S. has reportedly authorized Lenovo and Foxconn to act as distributors for H200 systems destined for China .
These companies could package the chips into servers or AI infrastructure products used by Chinese cloud providers and enterprise customers.
The approvals are part of a broader shift in U.S. export policy toward advanced AI chips.
Instead of automatically denying exports, the U.S. Commerce Department’s Bureau of Industry and Security now evaluates shipments of chips such as Nvidia’s H200 on a case‑by‑case licensing basis .
Key conditions attached to the framework include:
Nvidia has also reported obtaining a license for a limited number of H200 shipments to China, with exports subject to inspection and a 25% duty on sales under the current framework .
This system allows limited commercial sales while preserving U.S. oversight of advanced computing hardware flowing into China.
Despite U.S. clearance, the main bottleneck appears to be on the Chinese side.
Reports indicate that Chinese authorities have tightened scrutiny of foreign technology dependencies and are slowing or blocking imports of advanced AI hardware while promoting domestic semiconductor alternatives .
That means the transaction now depends on approvals and policy decisions from both governments. Even when U.S. export licenses are granted, shipments cannot proceed without Chinese import clearance and regulatory alignment.
The H200 situation reflects a broader strategic balancing act.
Washington wants to restrict China’s access to the most powerful AI hardware while still allowing some controlled commercial trade. Moving from a blanket ban to a managed licensing regime attempts to preserve U.S. oversight while protecting American semiconductor companies’ global revenue streams .
Beijing, meanwhile, is trying to reduce reliance on foreign chips and accelerate domestic alternatives. Policies that slow or scrutinize imports help encourage Chinese companies to adopt local hardware.
For Nvidia, the stalled shipments create uncertainty in one of the world’s largest AI infrastructure markets. Companies planning new AI clusters cannot rely on hardware that might remain stuck in regulatory review.
The pause also creates an opportunity for domestic competitors. Huawei and other Chinese chip developers are pushing AI accelerators aimed at replacing U.S. technology in local data centers. As Nvidia’s deliveries remain uncertain, Chinese cloud providers may invest more heavily in those alternatives.
In practice, the H200 deal has become more than a semiconductor sale—it is now a test case for how far advanced AI hardware can still move between the United States and China in an era of escalating technology competition.
Studio Global AI
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The U.S. has approved Nvidia to sell H200 AI chips to roughly 10 Chinese companies—including Alibaba, Tencent, ByteDance, and JD.com—but as of mid‑May 2026 no shipments have occurred because Chinese regulatory approva...
The U.S. has approved Nvidia to sell H200 AI chips to roughly 10 Chinese companies—including Alibaba, Tencent, ByteDance, and JD.com—but as of mid‑May 2026 no shipments have occurred because Chinese regulatory approva... Exports are allowed only under strict licensing: each shipment requires U.S. approval, compliance checks, and reportedly includes conditions such as inspection requirements and a 25% duty on sales [17][18].
The delay leaves Nvidia stuck in regulatory limbo in China while domestic alternatives—especially Huawei’s AI chips—gain time to expand adoption and ecosystem support [4][9].