In The AI Arms Race, China May Be Playing For Second Place

At Google’s annual showcase, the Chatbot Arena leaderboard — an influential crowdsourced benchmark hosted by nonprofit LMSYS on Hugging Face — highlighted notable advancements by Chinese AI models. Names such as DeepSeek, Tencent’s Hunyuan TurboS, Alibaba’s Qwen, and Zhipu’s GLM-4 weren’t just participants; they were leading contenders, particularly in demanding tasks like coding and complex dialogues. This change indicates that while U.S. companies like OpenAI and Google remain dominant overall, China’s AI ambitions are gaining undeniable momentum.

However, interestingly, China may not be striving to secure first place outright. Angela Zhang, a University of Southern California law professor and author of High Wire: How China Regulates Big Tech and Governs Its Economy, presents a contrasting viewpoint in a recent Financial Times essay. According to Zhang, Beijing might have strategically chosen to stay closely behind in AI to better serve its broader economic and geopolitical interests than aiming for outright supremacy.

This unexpected stance stems partly from recent aggressive U.S. actions restricting advanced semiconductor exports to China. By halting sales of critical chips like Nvidia’s H20, optimized for AI inference tasks, Washington aims to preserve its technological lead. Yet, these policies inadvertently push China to hasten its domestic semiconductor capabilities. Chinese firms such as Huawei and Cambricon have quickly filled the gap, with Huawei's Ascend 910c chip already achieving about 60% of Nvidia’s H100 inference performance.

Additionally, U.S. chip export controls have broader global ramifications, extending restrictions to key markets like India, Malaysia, and Singapore. In light of these challenges, emerging economies might increasingly lean toward China, indirectly boosting demand for Chinese technology.

In a significant policy change, the Trump administration recently revoked the Biden-era AI Diffusion Rule, which classified countries into tiers for AI chip exports. Instead, the administration has issued new guidelines stating that the use of Huawei’s Ascend AI chips — specifically models 910B, 910C, and 910D — anywhere in the world violates U.S. export controls. This move effectively imposes a global ban on these chips, citing concerns that they incorporate U.S. technology and thus fall under U.S. regulatory oversight. The Department of Commerce’s Bureau of Industry and Security emphasized that businesses worldwide must avoid using these chips or face penalties, including potential legal action. China has strongly condemned this unprecedented extraterritorial enforcement and has warned of legal repercussions for entities adhering to the U.S. directive, arguing that it violates international trade norms and China's development interests.

In response, China’s AI leaders have intensified efforts in semiconductor self-sufficiency. Huawei, for example, leads a coalition aiming for China to achieve 70% semiconductor autonomy by 2028. The recent unveiling of Huawei’s CloudMatrix 384 AI supernode — a system reportedly surpassing Nvidia’s market-leading NVL72 — marks a crucial milestone, addressing a critical bottleneck in China’s AI computing infrastructure.

Tencent’s strategy further exemplifies this strategic shift. During its May AI summit, Tencent introduced advanced models such as TurboS for high-quality dialogue and coding, T1-Vision for image reasoning, and Hunyuan Voice for sophisticated speech interactions. Additionally, Tencent has embraced open-source approaches, making its Hunyuan 3D model widely available and downloaded over 1.6 million times, highlighting China's dedication to fostering global developer communities.

Google’s former CEO Eric Schmidt recently noted that besides DeepSeek, China's most noteworthy models include Alibaba's Qwen and Tencent's Hunyuan. Their level has been quite close to Open AI's o1, which is a remarkable accomplishment.

USC’s Zhang suggests this positioning is intentional. Rather than provoking further escalations in U.S.-China tensions, Beijing seems content to develop robust domestic and international ecosystems around its technology. This approach aligns well with China's traditional focus on strategic autonomy and incremental innovation.

Open-source dynamics strengthen this calculated strategy. With lower technical barriers in AI inference — a rapidly growing market segment expected to account for 70% of AI compute demand by 2026, according to Barclays — China’s AI industry could benefit significantly from widespread adoption of its domestically developed solutions. Open-source releases from Chinese firms like DeepSeek and Baichuan also boost global developer engagement, potentially offsetting U.S. containment efforts by creating diverse, globalized ecosystems reliant on Chinese technology.

Nonetheless, it’s essential to recognize the challenges ahead. While Chinese models excel technically, global adoption remains limited, largely confined to domestic markets. Issues like interface design, user familiarity, and developer support still provide U.S.-based models with a distinct advantage internationally. Moreover, despite impressive hardware progress, China continues to lag behind the U.S. in software sophistication and ecosystem integration.

Nevertheless, the trend is unmistakable. China's foundational models are rapidly narrowing technical gaps. With strategic governmental backing and substantial investment in semiconductor self-sufficiency, China appears prepared not only to withstand U.S. sanctions but to flourish within their limitations.

Zhang’s perspective reframes the AI race less as a zero-sum game and more as a multipolar competition, where nations pursue strategic rather than absolute dominance. For China, being second might be more advantageous, reducing geopolitical friction while securing substantial economic benefits through technology self-reliance and international partnerships.

Ultimately, the AI landscape is evolving rapidly. Leadership in this field will increasingly depend on adaptability, global collaboration, and strategic foresight rather than solely on raw computing power. For now, China’s measured pursuit of second place might be precisely the kind of innovative thinking the tech world requires — less about outright dominance and more about sustainable and strategic competitiveness.

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