Çin çip ekosistemi baskılarla güçleniyor: ABD kısıtları işe yaramıyor, Huawei ve AI modelleri ivme kazanıyor

Kısaca

Çin, ABD kısıtlarına rağmen ekosistemini güçlendirdi; Huawei 2023'ten beri Kirin işlemcili cihazları 100 milyonun üzerinde sevk etti. Çinli yapay zeka modelleri, ABD yaklaşımlarıyla rekabet edebilir düzeye yaklaşıyor; DeepSeek ve Z.ai teknolojiye uyum sağladı. Gelecek dönemde AI uygulamaları için en ileri çiplere ihtiyaç azaldı; tedarik zincirinde çeşitlilik ve kendi çözümleri ön plana çıkabilir.

Ana mesele

ABD ihracat kontrollerinin Çin çip ekosistemini durduramadığı ve Çinli üreticilerin öne geçtiği bir tablo çıktı

Ne değişti?

Kontrollerin beklenen etkileri gerçekleşmedi; Çin kendi ekosistemini güçlendirme yönünde büyük adımlar attı

Beni nasıl etkiler?

Küresel rekabet dengesi değişebilir; teknoloji tedarik zincirlerinde yeni güvenlik ve yatırım kararları gerekecek

Ne oldu?

ABD ihracat kontrolleri uygulanmasına rağmen Çin çip ekosistemi güç kazandı.

Neden şimdi?

2022’den itibaren genişletilen kısıtlamalar sonrası Çin’in kendi ekosistemini kurma çabaları hızlandı.

Neden önemli?

Küresel rekabet dengesi değişebilir; ABD’nin tekelleri bağımlılıklar azalabilir veya artabilir.

Kimler etkileniyor?

• ABD ve Çinli çip şirketleri
• Huawei ve rakip Asya teknoloji oyuncuları
• Küresel yazılım geliştiricileri
• Tedarik zinciri tarafları

Sektör ve piyasa etkisi

Çip, yapay zeka yazılımı ve cihaz üretim piyasalarında rekabet ve yatırımlarda kayma bekleniyor.

Riskler

• Tedarik zinciri kırılganlığı artabilir
• ABD politikalarında değişiklik ihtiyacı doğabilir
• Teknoloji bağımlılıkları ve stratejik riskler artabilir

Takip edilmesi gerekenler

• Çin’in politika değişiklikleri ve yatırım rakamları
• Huawei’nin cihaz sevkiyatı ve Ascend ekosistemi gelişimi
• Mevcut AI modellerinin rekabet gücü
• ABD’nin kısıtlamalarıyla ilgili yeni adımlar

Haberin tamamı

“I’m not going to say ‘I told you so,'” says Rakesh Kumar. “But it really is ‘I told you so.'”

Kumar, a professor of electrical and computer engineering at the University of Illinois Urbana-Champaign and author of Chip Age: How Semiconductors Became the World’s Most Powerful Resource , has spent four years as one of Washington’s most persistent academic critics of its attempt to freeze China’s chip industry.

Days before the Biden administration unveiled its sweeping export controls on advanced chips and chipmaking equipment in October 2022—restrictions that have been expanded repeatedly since—he warned in Fortune that the crackdown would not work. “You can’t win an important race by hoping to trip your opponent, especially when there are significant costs to doing so,” he wrote. “A far better strategy is to run faster.”

Four years later, the controls don’t seem to have worked. Chinese processors are closing the gap with their U.S. rivals; the country’s AI models already match some of the U.S.’s best models.

Kumar’s first question is what the controls were ever supposed to achieve. “For most applications of AI, you don’t need the most advanced chips,” he tells Fortune .

Robotics, smart cameras, and other widely used AI applications don’t require the most advanced silicon. And by cutting China off, Washington gave Beijing every reason to build its own alternatives. “Export controls spurred China to invest all this money to set up an ecosystem where they can now serve these applications by themselves,” Kumar says. “Not only have export controls failed in that sense, but they’ve had the opposite effect.”

Huawei—once on the brink of death under U.S. sanctions—is now releasing premium smartphones and AI processors. On Oct. 13, it said it had shipped more than 100 million devices powered by its homegrown Kirin processors since 2023.

China is catching up on the software side, too. Chinese models are “very, very close, in terms of performance, to the models from the U.S.,” Kumar notes.

Chinese AI lab DeepSeek and startup Z.ai have adapted their flagship models to run on Huawei’s Ascend processors. Meituan, China’s food delivery giant, said in June it had trained a 1.6-trillion-parameter AI model entirely on domestically made chips. Nvidia’s share of data center chips in China fell to 34% in the first half of 2026, while shipments of its AI accelerators dropped by 44% compared to a year earlier, according to IDC data cited by Reuters .

In memory chips, Chinese chipmakers even claim to be ahead. ChangXin Memory Technologies (CXMT), China’s leading memory chipmaker, said at an industry conference in Shanghai over the weekend that it would debut a new memory chip architecture by the end of the year—one that, if proven, would put it ahead of current leaders Samsung , SK Hynix and Micron .

Washington’s stated goal has changed. U.S. officials talk less about stopping Chinese AI development than about keeping the U.S. at the frontier. They point to a growing list of workarounds: Nvidia’s top-end B200 and B300 processors, barred from export, keep turning up inside China; Anthropic and OpenAI accuse DeepSeek and other Chinese labs of “distilling” American models (training on a rival’s outputs to close the gap cheaply).

Kumar isn’t persuaded. “I see this in the policy discussion already,” he says. “They keep shifting the goalposts.”

Squeezing more out of what they have

“If it’s a strategic goal or a military goal—where you really need to have the most advanced models, need to be at par in terms of AI—then I think there are all these different ways in which you can achieve that goal,” Kumar explains.

China can offset what it lacks in advanced chipmaking equipment with algorithmic techniques, open-sourcing, and advanced packaging. “You may be doing that at higher cost, but that’s a cost that you’re willing to swallow if you think that this is important for the country,” he says.

Chinese chipmakers have never been able to import the extreme ultraviolet (EUV) lithography machines built by Dutch chip-equipment giant ASML—the tools that print the tiniest features on the most advanced chips—because the Dutch government, under U.S. pressure, has withheld an export license since 2019. That has forced fabs such as Semiconductor Manufacturing International Corp. (SMIC), China’s largest chipmaker, to rely on less sophisticated deep ultraviolet (DUV) machines, squeezing out better performance from older machines.

“How scalable is it? How much yield can you get out of it? Those are questions that we still don’t know the answer to,” Kumar says.

Rather than cram more transistors onto a single layer of silicon, Huawei is stacking chips in three dimensions. In May, He Tingbo, president of Huawei’s semiconductor business unit, unveiled the company’s answer to Moore’s Law: the “ Tau Scaling Law ,” which focuses on how fast signals move across a computing system over how small its transistors are, with a target of 1.4-nanometer-equivalent chip density by 2031.

Strategic vs. commercial

But while China’s chip self-sufficiency is a strategic success, it’s not necessarily a commercial one.

“Can Chinese companies be competitive against Western inference providers? The answer would likely be no, at least in the short term,” Kumar concedes.

That may sound counterintuitive, given that Chinese open-source models have won plaudits worldwide for their low costs—and that China has cheap power. But the biggest inference providers are still not Chinese, he points out. “These models get developed in China, but then they’re getting served on American chips, in America.”

“If the Chinese could also serve these tokens cheaper than the Americans, well, they would just serve these tokens from

Kaynaklar

• Fortune