The South China Morning Post’s editorial board published a striking assessment on July 28: China’s open-source AI strategy is “unstoppable,” and Washington’s fear of China’s AI progress is evident in “tired accusations and threatening sanctions.” The editorial, which carries the caveat that Alibaba, a major AI player, owns the newspaper, frames the Kimi K3 and Qwen3.8-Max-Preview releases as a “one-two punch” and a “second DeepSeek moment,” and argues that Hong Kong is positioned to be the most immediate beneficiary of China’s open-source AI surge.
The editorial’s core argument
The SCMP editorial board makes three interconnected claims. First, that China’s AI models, including Kimi K3 and Alibaba’s Qwen series, now outperform all competitors except the most advanced US models, and do so at a fraction of the cost. Second, that the open-source approach is strategically superior to the closed-source model favored by US frontier labs, because it allows for bespoke customization, reduces switching costs, and builds ecosystem lock-in through adoption rather than restriction. Third, that Xi Jinping’s call at WAIC for “a more open and inclusive approach to support AI in the Global South” and to avoid “a new historical injustice” in AI development is not rhetoric but strategy, and it is working.
The editorial is notable for its directness. It does not hedge on the geopolitical dimension: it frames the US accusations against Moonshot as “tired” and the threatened sanctions as evidence of fear rather than legitimate enforcement. It positions China’s open-source AI as a global public good and argues that the countries of the Global South are the natural constituency for that framing.
Hong Kong as the pivot point
The editorial’s most concrete policy argument concerns Hong Kong. Financial Secretary Paul Chan Mo-po is quoted arguing that Hong Kong is “ideal for AI commercialization” and can serve as a “springboard for mainland firms” seeking global markets. The editorial argues that Hong Kong’s combination of common law infrastructure, financial services depth, and proximity to mainland AI development makes it uniquely positioned to capture value from China’s open-source AI surge.
That argument has real substance. Hong Kong’s record export figures, reported today in our analysis of the HK$641 billion June trade surge, demonstrate that the territory is already capturing significant value from AI hardware flows. The question is whether it can also capture value from the software and services layer, the AI models, applications, and platforms that are increasingly where the economic value in AI is being created.
The Alibaba disclosure and what it means
The SCMP’s disclosure that Alibaba owns the newspaper is worth dwelling on. Alibaba is one of the companies whose AI models the editorial praises, Qwen3.8-Max-Preview is described as part of the “one-two punch” alongside Kimi K3. The editorial is, in effect, a major AI company’s newspaper arguing that its own AI strategy is unstoppable and that the US response to it is illegitimate.
That does not make the argument wrong. The SCMP editorial board has a track record of independent editorial judgment, and the core claims about China’s AI progress are well-supported by independent benchmarks. But it does mean that the editorial should be read as a strategic communication as much as an editorial opinion, a signal of how China’s AI industry wants the global open-source debate to be framed, directed at the international audience that reads the SCMP. As EastFrontier analyzed in its coverage of Xi’s open-source gambit at WAIC, China is playing a decade-long game for who owns the AI stack the developing world runs on, and editorials like this one are part of that game.
The open-source debate: what the SCMP gets right and what it elides
The editorial’s strongest argument is its empirical one: China’s open-weight models are genuinely competitive with the best closed-source models from US labs, and they are available at a fraction of the cost. Kimi K3’s performance on automation benchmarks, DeepSeek’s efficiency innovations, and Alibaba’s Qwen series have collectively demonstrated that the gap between Chinese and American frontier AI is narrower than most Western analysts expected two years ago. On that point, the SCMP is on solid ground.
What the editorial elides is the governance dimension. China’s open-source AI strategy is not purely altruistic: it is designed to build adoption, create ecosystem dependencies, and establish Chinese AI standards as the default for the Global South, all while China maintains tight domestic control over how AI is used within its own borders.
The AI companion ban that wiped out features for 345 million users in July, the five-agency regulations on AI anthropomorphic services, and the ongoing content moderation requirements for Chinese AI models are not mentioned in the editorial. The version of China’s AI strategy that the SCMP presents to its international audience is the open, inclusive, globally beneficial version, not the version that Chinese users experience domestically.
That gap between the international and domestic faces of China’s AI strategy is not unique to China, most countries present their technology policies in the most favorable light to international audiences. But it is worth noting, particularly for readers who are making decisions about which AI stack to build on. The openness of China’s AI models at the weights level does not necessarily translate into openness at the governance, data, or policy level, a distinction that matters for the Global South countries the SCMP editorial is implicitly addressing.
