As the war in Ukraine grinds on, the sanctions packages keep coming. On Friday, the EU passed its 18th package. Although the sanctions have provided obstacles for the Russian economy, they have not been able to stop Vladimir Putin from continuing his invasion. Nor are they the most significant factors in Russia’s current economic malaise, for which the level of war spending is far more responsible. Nevertheless, at least some of the measures in this relatively large package might have considerable influence on the course of any possible end to the conflict.

The most eye-catching part of the package is a significant change to the price cap on Russian oil exports. For crude oil, this has been a flat $60-a-barrel limit. In practice, however, the cap has not been that effective. When global crude prices are sufficiently high, Russian oil has frequently sold above the cap. When prices are sufficiently low, Russian crude sells below the cap.

This latter situation, with the cap rendered irrelevant because of low global oil prices, is where the West finds itself today. The EU’s response has been to try and replace this cap with a dynamic one: instead of a flat rate, it now depends on global oil prices. The new price cap is 15% below an average reference global oil price, and will come into effect on 3 September. If it were to happen today, it would drop the cap to $47.60 a barrel.

In practice, however, this is unlikely to do much on its own. When the cap was first created, the US was on board. In fact, the Biden administration encouraged it as an alternative to more drastic measures against Russia’s oil industry. Without US involvement, though, the country will be unable to control the banks which clear payments directly. What’s more, the new dynamic cap only mirrors the status quo. Russian oil already tends to sell at a discount compared to global oil prices, because the loss of Europe as a market has pushed Moscow into a quasi-monopsonistic situation with the two biggest buyers of its crude: China and India.

What is significant, however, is what might happen with Nord Stream — or, rather, what won’t, because of the sanctions. The new sanctions ban any transactions related to the pipelines meaning that, as long as these sanctions are in place, any future possibility of anything changing with Nord Stream is effectively nil.

This will not matter much in the short term. But we already know that the US and Russia discussed trying to restart Nord Stream in the event of a peace deal. This was already looking difficult before the sanctions came into place, but now the EU is very firmly shutting the door on that prospect.

The even bigger measure, however, is still making its way through the legislative machinery of Brussels. This is an initiative to end all Russian fossil fuel imports, including gas, by the end of 2027. Taking a future energy relationship between the EU and Russia completely off the table may impact the overall environment in which any negotiations take place. Whatever happens, Russian oil will play an outsized role in the resolution of this war.

This is an edited version of an article originally published in the Eurointelligence newsletter. 

China is trying to catch up with America on artificial intelligence. The Wall Street Journal has reported that Zhipu AI — one of China’s six “AI tiger” LLMs — has released a new model that can rival leading US systems, including Anthropic’s Mythos, in cybersecurity tasks such as pinpointing security bugs. While this marks a milestone in China’s drive to catch up with Western AI capabilities, strong performance on a single benchmark does not mean it has taken the lead. Chinese models still lag behind their Western counterparts in broader capabilities, such as autonomous operation. Skepticism is therefore warranted before resorting to hysterical conclusions, but complacency about the geopolitical implications of China’s AI advances would be an even greater mistake.

On the infrastructure side, Chinese AI is still constrained by access to advanced chips, with American labs way ahead in computing capacity as well as investment. Analysis from earlier this year suggests that Chinese models are likely to be at least a few months behind those in the US. But they are still continuing to make progress, or that the geopolitical importance of AI will be decided only by whose LLM has ventured deeper into the technological frontier. The practical applications of AI, countries’ to capture foreign markets, and the application of AI into the real economy will matter just as much.

Here, China may hold an advantage. As with its dominance across many critical supply chains, Beijing may not need to produce the most advanced AI systems — only those that are affordable and widely deployable. In doing so, it could consolidate global influence by supplying functional, low-cost AI at scale.

Beijing seems to be pursuing exactly that path, developing an AI “open-source” strategy that offers affordable, widely available AI models for companies and individuals to use and modify as they wish. The production of the DeepSeek AI model, which matched the performance of Silicon Valley tools such as ChatGPT at a fraction of the cost for users, created goodwill among Chinese models with developers.

The four most popular models on OpenRouter, an AI hardware platform for developers, are now all Chinese. The goal for China is not only to win the frontier-model race, but to make its systems the default layer of AI adoption across industries and global markets. For most economies, the choice is increasingly between an affordable tool they can deploy now and a more robust one that may be out of reach.

And while the countries adopting Chinese models may be exposed to political pressure and cyber threats from Beijing, safer and more capable alternatives matter little if they are unaffordable. American AI companies are already under pressure to monetize products whose operating costs are rising. If Chinese open-source models become the cheap default for startups, universities, governments and businesses across the developing world, then America’s AI lead will be eroded from below.

Perhaps more concerning for America in the long run is how AI can give Chinese manufacturing even more strength, through the ongoing integration of AI as a general-purpose technology. China’s new Five-Year Plan mentioned AI more than 50 times and includes an “AI+” action plan aimed at spreading AI across the economy.

Beijing has been pioneering automation of its critical infrastructure for years, with promising recent results in increasing warplane production capacity. In that regard, China’s open-model strategy and manufacturing dominance will reinforce each other. Cheap, adaptable models accelerate deployment across the real economy while those deployments generate real-world data and use cases that can feed back into further model improvement.

The United States should not dismiss the importance of its lead in the AI race. That lead worries Beijing, not least because a more automated Chinese economy would also become more vulnerable to AI-generated cyber threats. But nor should Washington assume that China cannot catch up with American capabilities over time.

This AI competition represents part of a broader struggle over tech supply chains and geopolitical influence. Decisions over whether to adopt US or Chinese models could produce a more fragmented global reality, with different regions relying on different cloud providers, chips and security structures. The result will likely be a global economy which is divided into competing spheres, rather than one which produces a single winner.

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Miquel Vila is a political and geopolitical risk consultant focusing on industrial strategy, critical infrastructure and global supply chains.

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