Nvidia Chip Approval Could Strengthen China’s Artificial Intelligence Capabilities
The United States’ approval of exporting Nvidia’s H200 chips to China marks a significant shift in US technology and export-control policy, a move that could reshape the trajectory of China’s artificial intelligence sector despite ongoing geopolitical and technological tensions.
On Monday, the White House approved Nvidia’s request to sell its H200 processor to China, currently the most powerful and advanced AI chip that Chinese firms can legally acquire. Under the arrangement, the US government will receive 25% of the revenues from each sale. Nvidia’s shares rose more than 2% following initial reports of the decision and extended gains in after-hours trading after official confirmation.
The H200 chip is particularly well-suited for AI inference, the process of running queries and generating outputs from trained models, due to its high-bandwidth memory capabilities. Since 2022, US export controls have focused primarily on limiting advanced AI training by capping overall compute performance, while memory bandwidth constraints were addressed only indirectly until later regulatory updates.
Inference, however, is increasingly seen as the decisive factor in determining the real-world economic impact of artificial intelligence. Large-scale deployment and integration of AI across industries depend heavily on inference performance, where memory bandwidth represents the main bottleneck.
Although optimized for inference, the H200 remains a highly capable training chip, as it is an advanced iteration of Nvidia’s previous flagship AI processors. This dual capability gives it strategic importance for Chinese AI developers operating under hardware constraints.
Inference Demand Outpaces Training
Unlike model training, which typically occurs once or infrequently, inference operations are performed billions of times daily. Estimates suggest that inference accounts for between 60% and 90% of total AI computing and energy consumption over the lifecycle of deployed systems. As a result, cumulative inference workloads ultimately exceed training demands, making memory capacity and bandwidth critical resources.
In this context, the H200 represents a substantial leap over the H20, the most advanced Nvidia chip previously available to China, particularly in training performance. While Huawei’s latest Ascend chips may rival Nvidia’s offerings in certain training benchmarks, China’s overall AI capacity remains constrained by limited domestic production. US estimates place China’s local output at around 200,000 advanced chips this year, although Huawei’s roadmap points to rapid future expansion.
Access to the H200 could therefore ease major bottlenecks in both training and inference, accelerating the deployment of AI applications across the Chinese economy.
Alignment with Beijing’s AI Strategy
China’s national AI governance strategy prioritizes application-driven development, emphasizing the integration of existing capabilities across sectors rather than focusing solely on raw model performance. The H200’s high memory bandwidth aligns closely with this approach, enabling more efficient inference and large-scale deployment in areas such as manufacturing, finance, healthcare, and public services.
Advanced inference models are often memory-bound, as they reason step by step through complex tasks. Performance in such systems depends heavily on memory capacity and bandwidth, areas where the H200 offers a clear advantage.
Chinese chipmakers, including Huawei, continue to face challenges in accessing high-bandwidth memory due to US export restrictions on suppliers such as Samsung and SK Hynix. While industry reports suggest Huawei has stockpiled enough high-bandwidth memory to support near-term production plans, access to Nvidia’s H200 could effectively mitigate China’s broader memory constraints.
A Shift in US Strategy
The H200 decision, alongside earlier approval of the H20, highlights a shift in Washington’s approach from outright technological denial toward controlled access. While training restrictions remain stringent, US policymakers appear increasingly focused on maintaining global market dominance and technological influence rather than fully excluding China from advanced hardware.
The underlying rationale is that preserving US leadership in AI exports and keeping Chinese firms dependent on American technology may strengthen the US AI ecosystem more effectively than a complete ban. The revenue-sharing mechanism further reinforces this strategy.
At the same time, the decision reflects a compromise within the US administration. According to US media reports, internal opposition prevented approval of Nvidia’s newer Blackwell-based processors ahead of recent US-China talks. Allowing sales of the Hopper-based H200, while excluding Blackwell and future Rubin architectures, provides a middle ground between security concerns and commercial interests.
Implications for China’s AI Sector
While Beijing has at times discouraged purchases of US chips in favor of domestic alternatives, it may prove difficult for Chinese AI companies to forgo the H200 given its substantial performance gains and memory advantages. With H200-class infrastructure, Chinese cloud and AI service providers could deliver globally competitive AI services at lower cost and train more efficient models, even under continued hardware restrictions.
Ultimately, the policy shift underscores a broader recalibration of US-China technology relations, where managed access replaces blanket exclusion. Whether this approach slows or accelerates China’s long-term push for AI self-sufficiency remains an open question, but in the near term, Nvidia’s H200 is poised to give China’s AI ecosystem a meaningful boost.