China is leveraging state-supported companies to release powerful, open-source AI models at drastically lower prices. The core strategy is not to build the single best model, but to commoditize the market, capture global usage, and undermine the pricing power of Western competitors.

While the US pursues cutting-edge AGI, China is competing aggressively on cost at the application layer. By making LLM tokens and energy dramatically cheaper (e.g., $1.10 vs. $10+ per million tokens), China is fostering mass adoption and rapid commercialization. This strategy aims to win the practical, economic side of the AI race, even with less powerful models.

China's strategy for AI dominance is not to build superior models, but to proliferate its own cheap, open-weight AI models globally. By offering free technology and training, especially in the Global South, China aims to establish its standards and geopolitical influence.

China is gaining AI market share by releasing powerful models at a fraction of US costs. This mirrors its historical industrial strategy of leveraging lower costs and subsidies to dominate global markets, posing a significant geopolitical and economic threat to American AI leadership.

China's strategy of releasing free, powerful AI models is an economic counterattack to US chip controls. It cannibalizes the market for paid API access from US leaders like OpenAI, hitting their revenue and slowing R&D, thereby neutralizing the American technological advantage.

In a strategic paradox, China is championing open-source AI. This is not about openness; it's a "turbo dumping strategy" to flood the global market with free AI, preventing American companies from monetizing their proprietary models and establishing market leadership.

While US firms lead in cutting-edge AI, the impressive quality of open-source models from China is compressing the market. As these free models improve, more tasks become "good enough" for open source, creating significant pricing pressure on premium, closed-source foundation models from companies like OpenAI and Google.

China's strategy for winning the AI race is not about building the most advanced model, but about mass distribution of lower-cost, 'good enough' open-weight models. By prioritizing volume and accessibility, they capture the majority of token usage and achieve market dominance.

China is compensating for its deficit in cutting-edge semiconductors by pursuing an asymmetric strategy. It focuses on massive 'superclusters' of less advanced domestic chips and creating hyper-efficient, open-source AI models. This approach prioritizes widespread, low-cost adoption over chasing the absolute peak of performance like the US.