The U.S. Charges for Its AI, Prioritizing Immediate Profits. China Offers It for Free, Focusing on the Coming Decades

There’s an intriguing paradox in the current development of AI that reflects more about geopolitics than technology:

• The U.S., traditionally a leader in proprietary software and premium monetization, is developing closed AI models.
• China, which has historically been more restrictive regarding the flow of information, is at the forefront of open source AI.

This investment is no coincidence. Each bloc adopts the strategy that best serves its structural interests.

→ The U.S. (with companies such as OpenAI, Anthropic, and Google) is creating the equivalent of the iPhone for AI:

• Highly sophisticated systems
• Vertical integration
• Polished premium experiences that justify charging for access

The rationale is clear. When you control the best GPUs, leading cloud services, and have the capital to train the most advanced models, monetizing that advantage through paid APIs makes immediate economic sense. This model has sustained the American software industry for decades.

→ In contrast, China, with companies such as DeepSeek, Qwen, and MiniMax leading the open model ranking, is developing the Android of AI:

• A free and modifiable ecosystem
• Downloadable for local use without reliance on paid APIs
• Permissive licenses without business restrictions, unlike Meta’s approach with Llama
• Accessible source code for independent research and development

This approach isn’t altruistic, nor is it solely due to cultural differences. It’s a strategic move aimed at creating global dependence on a Chinese technology stack when the American one becomes less accessible. The goal is to present it as a highly attractive alternative, even before its results are evident.

Llama is American and also ranks among the top open source models (with significant caveats). However, a plausible hypothesis is that Meta released it as a response to falling behind, employing a classic defensive strategy aimed at eroding the leaders’ advantage.

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Growing strength. China is approaching the AI race from a position of growing strength while also facing restrictions on access to hardware and Western markets. When a rival controls critical technologies such as chips and cloud platforms, the only way to create an alternative ecosystem is to make it so appealing that the world can’t ignore it.

This strategy reflects a form of technological soft power, where resources are given away today to secure dominance in the future. Alternatively, China could focus on developing its vast domestic market and expanding into new markets. This is how Huawei moved away from mere competition to building a parallel reality.

The numbers are telling. According to benchmarks from Artificial Analysis, the three leading open source models are emerging from China. Startups are opting for DeepSeek instead of GPT. Southern Hemisphere countries are utilizing Chinese models because they’re offered for free. Universities are training with Qwen instead of Claude. All this contributes to an ecosystem that the U.S. can’t censor, regulate, or disconnect unilaterally.

This scenario mirrors China’s gradual independence from GPS. In two decades, the country hasn’t only become less reliant on GPS but has also expanded its BeiDou navigation system to 140 countries.

However, both strategies have their pitfalls:

• The U.S. model generates immediate revenue but encourages the rest of the world to seek alternatives, especially as trade tensions rise. This fosters competition.
• The Chinese model attracts users but will eventually need to monetize without alienating its base.

Google learned this lesson the hard way with Android. After capturing 70% of the market, it began to monetize aggressively. It also faced massive fines in Europe and antitrust lawsuits in the U.S. Additionally, competition from Chinese alternatives like Huawei’s HarmonyOS started to emerge. The cycle came full circle.

The key takeaway is that giving away technology to cultivate dependency can be effective, but monetizing that dependency once established can draw unwanted regulatory attention. This is a dilemma that China will inevitably face with its “free” AI models.

The real battle lies not in having the best AI today but in controlling tomorrow’s intellectual infrastructure.

• The U.S. sells AI as a premium service.China offers AI as a universal operating system.

The outcome will hinge on a clash between two historically successful but contrasting philosophies: America’s emphasis on aggressive monetization versus China’s patience in investing for decades to achieve leadership. This sets up a tension between immediate revenue and long-term dependency.

Only time will tell how this conflict unfolds.

Image | Igor Omilaev

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