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08.12.2025

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08.12.2025

Why China is going all-in to win its version of the AI race

07.12.2025
Economy
Why China is going all-in to win its version of the AI race
Why China is going all-in to win its version of the AI race

China is accelerating spending, standards and model development to win a contest that prioritizes widespread adoption rather than dominance in frontier models.

Macquarie Research says new company results, model launches and policy steps in November reinforce Beijing’s push to wire the real economy with dense, affordable and locally anchored AI infrastructure, even as the U.S. extends its lead at the cutting edge.

Macquarie argues that China has “set a different finish line,” focusing on diffusion across cloud services, consumer apps, advertising and enterprise workloads.

That strategy depends less on matching the U.S. in advanced GPUs and more on scaling clusters through cheaper networking components and mass manufacturing.

The brokerage says China remains behind the U.S. in chips and proprietary fabrics, but it has moved far ahead in optical modules, a layer that determines how efficiently accelerators can be connected.

The clearest signal of this approach is the addition of Innolight to Macquarie’s China AI infrastructure basket. Analysts call the company a global leader in 800G modules and a key supplier for 1.6T systems, noting that its silicon-photonics designs can cut the bill of materials by up to 50%.

Innolight already produces roughly half its high-speed capacity outside China to serve U.S. cloud demand, which Macquarie says positions it as a central node in both countries’ AI supply chains.

Corporate results across China’s internet and hardware sectors also point to a deliberate nationwide buildout.

Baidu reported that AI-empowered revenue from cloud, apps and ads is growing more than 50% year over year, while Tencent said new AI features are already monetising.

Alibaba’s September-quarter cloud revenue accelerated into the mid-30s % year over year on demand for QWEN-powered services, reflecting what analysts describe as diffusion into mainstream cloud workloads.

GDS continued to expand 100MW-class data-centre campuses, and both Luxshare and Lenovo increased investment in AI servers, optics and thermal systems.

On the policy front, the Ministry of Industry and Information Technology closed consultation on nationwide computing-power standards on November 22, offering a unified framework for infrastructure, networks and “green” data centres.

Analysts say this provides visibility for operators building out non-frontier AI systems across provinces.

Meanwhile, Moonshot AI’s launch of the Kimi K2 Thinking model on November 6 pushed China into the top five of global intelligence rankings compiled by Artificial Analysis, supporting the view that the frontier gap remains narrow even as U.S. models like Gemini 3 Pro and Claude 4.5 continue to lead.

Macquarie notes that China’s move is not without constraints. Companies are still limited by chip supply, and domestic-only strategies carry cost and efficiency penalties.

November also saw an about 8% decline across China’s AI infrastructure basket, echoing global concerns about an “AI bubble.”

But the brokerage says spending plans, R&D commitments and model progress “still looks more like a state-backed push for ’good-enough’ AI everywhere,” underlining China’s decision to compete through scale and accessibility rather than frontier breakthroughs.

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