Washington is preparing to issue an ultimatum to dozens of countries: decide whose side you are on in the technological confrontation with China. However, behind this seemingly tough diplomatic démarche lies not confidence in its own strength, but a deep structural crack in the American model of artificial intelligence.
An Ultimatum as a Symptom
This concerns a letter that the State Department sent to 35 countries that had previously signed the American declaration on AI opportunities. Those who choose the Chinese side are threatened with exclusion from the Pax Silica initiative — a project to control supply chains for chips, semiconductors, and critical minerals, launched a year earlier. About two dozen states have joined the American project. Kazakhstan draws particular attention, having entered both coalitions simultaneously and now being under close scrutiny from Washington.
Beijing is acting symmetrically: Chairman Xi Jinping announced the creation of a World Organization for AI Cooperation, promoting Chinese technology as an alternative to American influence. The balance of power is already ambiguous. The US retains primacy in fundamental research and the development of advanced models, but China is rapidly closing the gap in efficiency, applied use, and robotics.
An Economy That Doesn't Add Up
The key vulnerability of the American approach is the gap between investment and real returns. Since 2023, US tech giants have poured hundreds of billions of dollars into AI, but monetization remains minimal. Microsoft's capital expenditures have reached $116 billion, while direct revenue from its AI business is estimated at $40–45 billion. The ratio of investment to revenue has jumped from the usual 7–10% to 35%, and cash flow over seven years has grown only 1.6 times against a 2.7-fold increase in revenue.
Competitors are in no better shape. Google posted its first negative operating cash flow, halted share buybacks, and over fifteen months grew its debt from $30 billion to $120 billion. Amazon went $25 billion into the red over six months, and Meta spends 97% of its operating cash flow on AI. Direct revenues are incomparable to the scale of costs: Microsoft 365 Copilot gathered about 30 million subscriptions against investments of $190 billion, while Google's potential revenue from subscriptions and APIs is estimated at $15–20 billion against investments of $200 billion.
This entire structure rests on hope: after market consolidation, American companies will dictate prices and recoup their costs. It is precisely this prospect that China is destroying, zeroing out the economic profitability of American giants.
China's Bet on Cheapness
Instead of racing for "intelligence" at any cost, Chinese developers have bet on efficiency and open access. A striking example is DeepSeek V4 Flash: the model costs almost nothing, about $0.08 per million input tokens, yet delivers performance on par with American flagships from spring 2026. The response was forced price cuts by OpenAI. The GLM-5.3 model from Z.ai, at a price of about $2.5 per million tokens, has reached a level between GPT-5.5 and GPT-5.6 and is optimized for Huawei's Chinese accelerators, reducing dependence on Nvidia.
The result has directly impacted the market: a year ago, American models accounted for 75–85% of requests; now, 60–70% of token traffic is provided by Chinese solutions — DeepSeek, GLM, and others. The reason is simple: for mass tasks like code generation, data processing, and agentic execution, expensive "genius" is not needed. What is required is reliability, speed, and low price — and all of this is offered by China. By releasing powerful models almost for free, Beijing devalues American investments: each such release pushes the price bar down and deprives the US of the ability to recoup its enormous investments.
Parity and the Price of Isolation
The quality gap, on which Americans counted to maintain a premium, has nearly disappeared in the mass segment. Flagships like GPT-5.6 and Opus-5 still lead in complex tasks, but models like Kimi K3, GLM-5.3, and Qwen-3.8 have come very close to them, working noticeably faster and cheaper. At this pace, China could move ahead as early as 2027. Google's position is telling: possessing data, chips, and engineers, the company lost its leadership and is now playing catch-up with cheap models and dumping — a systemic flaw of the American approach, betting on the scale of computation without proper optimization.
It is this economic weakness that pushes Washington toward political measures. The demand to choose a side is a sign of vulnerability: the US is trying to administratively isolate China from the global market, since it can no longer maintain sales of expensive models through market means. Such a strategy carries serious risks: the world could split into two technological blocs with duplicative standards, developing countries, due to coercion, could demonstratively leave the American coalition, and restrictions will only accelerate China's development of its own chips and algorithms.
The final picture is paradoxical. In terms of investment, the US is far ahead, but that money is not paying off and is increasing debt; in terms of actual use, China already dominates the mass segment; in terms of technology, parity has been reached with a trend not in America's favor. Administrative barriers rarely work if a competitor's product is cheaper and good enough, so artificial isolation risks only accelerating the formation of an independent Chinese AI bloc.
My view: For the crypto industry and decentralized technologies, this split is not just a geopolitical drama. It creates demand for neutral, open infrastructure not controlled by either bloc. In the long term, it is precisely the cheap and open models promoted by China that could become the basis for a new generation of decentralized AI applications, opening a window of opportunity for crypto projects building independent computing networks.