In mid-August, information emerged that Washington is preparing to present an ultimatum to dozens of countries: decide whose side you are on in the technological confrontation with China. Formally, this looks like another round of superpower rivalry, but behind the political gesture lies a much deeper problem. Executive Director of RAKIB Alexander Brazhnikov believes that this ultimatum is not a show of strength, but a sign of a structural crisis in the American artificial intelligence model.
The Ultimatum and the Balance of Power
The State Department has prepared a letter for 35 countries that previously signed the American "Statement on AI Capabilities." Those who choose the Chinese side face exclusion from the Pax Silica initiative—a project to control supply chains for models, semiconductors, and critical minerals. About two dozen states have joined the American initiative. Kazakhstan deserves special attention: the country has joined both coalitions at once, and it is precisely its dual position that has caused concern in Washington. To date, it is the only participant that is simultaneously a member of both the American and Chinese structures.
Beijing, for its part, is acting symmetrically. In the summer, Chinese President Xi Jinping announced the creation of a World Organization for AI Cooperation, promoting Chinese technology as an alternative to American influence in the industry.
According to Brazhnikov's assessment, the balance of power is already ambiguous. The United States maintains its lead in fundamental research, the development of advanced models, and the volume of investments, but China is rapidly closing the gap—primarily in efficiency, applied technology use, and robotics.
An Economy That Does Not Add Up
The expert sees the key vulnerability of the American approach in the gap between investments in infrastructure and real returns. Since 2023, US technology giants have poured hundreds of billions of dollars into AI, but monetization remains minimal. The numbers speak for themselves: Microsoft's capital expenditures reached $116 billion over the year, while direct revenue from its AI business is estimated at $40–45 billion. The investment-to-revenue ratio 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.
The position of competitors is no better. Google showed negative operating cash flow for the first time in history, halted share buybacks, and over fifteen months increased its debt from $30 billion to $120 billion. Amazon went negative by $25 billion in cash flow over six months, while Meta spends 97% of its operating cash flow on AI.
Direct revenues are incomparable to the scale of costs. Microsoft 365 Copilot has gathered about 30 million subscriptions against investments of $190 billion; Google's potential revenue from subscriptions and APIs is estimated at $15–20 billion with investments of $200 billion. Meta's advertising, thanks to AI, adds only about 1% in conversions. This entire structure, according to Brazhnikov, is held together by hope: after market consolidation, American companies expect to dictate prices and finally recoup their costs. It is precisely this prospect that China is destroying.
China's Bet on Cheapness and Openness
Instead of racing for "intelligence" at any cost, Chinese developers have bet on cost efficiency and open access. A clear example is DeepSeek V4 Flash: the model costs almost nothing, about $0.08 per million input tokens, but delivers performance on par with American flagships from spring 2026. The response was forced price cuts from 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 versions and is additionally optimized for Huawei's Chinese accelerators, reducing dependence on Nvidia.
The result has directly impacted the market. According to data from the largest traffic router, OpenRouter, a year ago American models accounted for 75–85% of requests, but now Chinese solutions—DeepSeek, GLM, and others—provide 60–70% of token traffic. The reason is simple: for mass tasks such as code generation, data processing, and agentic execution, businesses do not need expensive "genius." What is required is reliability, speed, and low price—and all of this is offered by China.
By releasing powerful models almost for free, China devalues American investments: each such release pushes the price bar down and deprives the United States of any chance to ever recoup its enormous investments.
Technology Parity and the Price of Isolation
The quality gap, on which the Americans counted to maintain a premium, has almost disappeared in the mass segment. Flagships like GPT-5.6 and Opus-5 still lead in the most complex tasks such as scientific reasoning, but models like Kimi K3, GLM-5.3, and Qwen-3.8 have come very close to them while working noticeably faster and cheaper. Brazhnikov suggests that at this pace, China could move ahead as early as 2027.
The expert calls Google's position especially telling: possessing data, chips, and engineers, the company still lost its leadership and is now trying to catch up through cheap models and dumping. This points to a systemic flaw in the American approach—a reliance on the scale of computation without proper optimization.
It is economic weakness that is pushing Washington toward political measures. The demand to choose a side is a sign of vulnerability: the United States 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 would only accelerate China's development of its own chips and algorithms.
The final picture is a paradox. In terms of investments, the United States is far ahead, but this money is not paying off and is increasing debts; in terms of real usage, China already dominates the mass segment; in terms of technology, parity has been achieved with a trend not in America's favor. Administrative barriers rarely work when 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 technology markets, this situation means one thing—cheap and open AI models will become the new standard, and this will directly affect the cost of computing, decentralized projects, and tokens tied to infrastructure. Investors should closely monitor Chinese developments: it is they who are currently setting the trend that will reshape the global technological landscape.