{"id":730823,"date":"2026-06-01T16:00:36","date_gmt":"2026-06-01T13:00:36","guid":{"rendered":"https:\/\/buradabiliyorum.com\/en\/us-export-curbs-push-chinas-ai-chips-away-from-gpus-to-custom-asics\/"},"modified":"2026-06-01T16:00:36","modified_gmt":"2026-06-01T13:00:36","slug":"us-export-curbs-push-chinas-ai-chips-away-from-gpus-to-custom-asics","status":"publish","type":"post","link":"https:\/\/buradabiliyorum.com\/en\/us-export-curbs-push-chinas-ai-chips-away-from-gpus-to-custom-asics\/","title":{"rendered":"US export curbs push China&#8217;s AI chips away from GPUs to custom ASICs"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_89 counter-hierarchy ez-toc-counter ez-toc-custom ez-toc-container-direction\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<label for=\"ez-toc-cssicon-toggle-item-6aef264e7833f\" class=\"ez-toc-cssicon-toggle-label\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #dd3333;color:#dd3333\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #dd3333;color:#dd3333\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/label><input type=\"checkbox\"  id=\"ez-toc-cssicon-toggle-item-6aef264e7833f\" checked aria-label=\"Toggle\" \/><nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><ul class='ez-toc-list-level-4' ><li class='ez-toc-heading-level-4'><ul class='ez-toc-list-level-4' ><li class='ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/buradabiliyorum.com\/en\/us-export-curbs-push-chinas-ai-chips-away-from-gpus-to-custom-asics\/#TLDR\" >TL;DR<\/a><\/li><\/ul><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/buradabiliyorum.com\/en\/us-export-curbs-push-chinas-ai-chips-away-from-gpus-to-custom-asics\/#Three_paths_to_custom_chips\" >Three paths to custom chips<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/buradabiliyorum.com\/en\/us-export-curbs-push-chinas-ai-chips-away-from-gpus-to-custom-asics\/#Performance_is_no_longer_the_bottleneck\" >Performance is no longer the bottleneck<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/buradabiliyorum.com\/en\/us-export-curbs-push-chinas-ai-chips-away-from-gpus-to-custom-asics\/#The_software_stack_problem\" >The software stack problem<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/buradabiliyorum.com\/en\/us-export-curbs-push-chinas-ai-chips-away-from-gpus-to-custom-asics\/#A_structurally_different_ecosystem\" >A structurally different ecosystem<\/a><\/li><\/ul><\/nav><\/div>\n<p><img decoding=\"async\" src=\"https:\/\/media.thenextweb.com\/2026\/06\/china-ai-chip-asic-gpu-nvidia-export-controls.avif\" \/><\/p>\n<div id=\"article-main-content\">\n<p><em><\/p>\n<div class=\"postContent-tldr\">\n<h4 class=\"postContent-offsetTitle\"><span class=\"ez-toc-section\" id=\"TLDR\"><\/span>TL;DR<span class=\"ez-toc-section-end\"><\/span><\/h4>\n<p>US export controls are pushing China\u2019s AI chip industry away from <a href=\"https:\/\/buradabiliyorum.com\/en\/category\/general\/\" data-internallinksmanager029f6b8e52c=\"3\" title=\"General\" target=\"_blank\" rel=\"noopener\">general<\/a>-purpose GPUs and toward custom ASICs. Huawei leads with 62% projected market share, while Alibaba and Cambricon pursue alternative architectures that may create a structurally different ecosystem from the Nvidia-dominated West.<\/p>\n<\/div>\n<p><\/em><\/p>\n<p>China\u2019s AI chip industry is no longer trying to build an Nvidia clone. Under sustained US export controls that block access to the most powerful general-purpose GPUs, the country\u2019s largest <a href=\"https:\/\/buradabiliyorum.com\/en\/category\/technology\/\" data-internallinksmanager029f6b8e52c=\"4\" title=\"Technology\" target=\"_blank\" rel=\"noopener\">technology<\/a> companies are pivoting toward <a href=\"https:\/\/buradabiliyorum.com\/en\/category\/download-scripts-themes-apps\/\" data-internallinksmanager029f6b8e52c=\"9\" title=\"Download Scripts &amp; Themes &amp; Apps\" target=\"_blank\" rel=\"noopener\">app<\/a>lication-specific integrated circuits, custom chips designed to do one thing extremely well rather than handle any workload. The shift is creating a domestic semiconductor ecosystem that may end up architecturally distinct from the Nvidia-dominated model that powers AI in the West.<\/p>\n<p>At the centre of this divergence is a design choice that export controls have accelerated. General-purpose GPUs, the kind Nvidia sells, are flexible and programmable, making them ideal for the fast-moving research phase of AI development where model architectures change constantly. ASICs sacrifice that flexibility for raw efficiency,\u00a0delivering faster performance at lower power consumption\u00a0for specific AI tasks. In a market where the best Nvidia hardware is unavailable, the economics of custom silicon become far more compelling.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Three_paths_to_custom_chips\"><\/span>Three paths to custom chips<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Chinese companies are pursuing three distinct ASIC architectures. Huawei is betting on neural processing units through its Ascend <a href=\"https:\/\/buradabiliyorum.com\/en\/category\/watch-movies-tv-seriess\/\" data-internallinksmanager029f6b8e52c=\"8\" title=\"Watch Movies &amp; TV Series\" target=\"_blank\" rel=\"noopener\">series<\/a>, including the widely deployed 910C and the upcoming Ascend 950. Cambricon Technologies is building domain-specific architectures with its Siyuan 590 and 690 series. Alibaba is taking a third route through its semiconductor unit T-Head, which launched the Zhenwu M890 parallel processing unit at its annual cloud computing summit last week, claiming three times the performance of its predecessor.<\/p>\n<div class=\"inarticle-wrapper channel-cta\">\n<div class=\"ica-text\">\n<p class=\"ica-text__title\">TNW City Coworking space &#8211; Where your best work happens<\/p>\n<p>A workspace designed for growth, collaboration, and endless networking opportunities in the heart of tech.<\/p>\n<\/div>\n<\/div>\n<p>On the GPU side, Moore Threads leads the domestic effort. Founded in 2020 by Zhang Jianzhong, Nvidia\u2019s former China executive, the company has dedicated itself to general-purpose chips like the MTT S5000 series. Biren Technology, Enflame, and Iluvatar CoreX are also competing in the space, but none has achieved the scale of the ASIC leaders.<\/p>\n<p>A\u00a0<a rel=\"nofollow\" target=\"_blank\" href=\"https:\/\/www.tomshardware.com\/tech-industry\/huawei-expects-12-billion-in-ai-chip-revenue-this-year-as-nvidias-china-market-share-hits-zero\" target=\"_blank\" rel=\"nofollow noopener\">Morgan Stanley report published on 8 May<\/a>\u00a0made the market dynamics clear. Huawei is projected to capture 62% of China\u2019s domestic AI accelerator market in 2026, followed by Cambricon at 14%. Among big tech firms building proprietary chips, Baidu and Alibaba are each expected to take roughly 5%. The ASIC heavyweights are winning on volume and momentum.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Performance_is_no_longer_the_bottleneck\"><\/span>Performance is no longer the bottleneck<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>The performance gap between Chinese chips and Nvidia\u2019s export-compliant hardware has narrowed significantly. Morgan Stanley data shows that Huawei\u2019s Ascend 950 cards and Cambricon\u2019s Siyuan 690 can outperform Nvidia\u2019s H20, the most powerful chip Nvidia is currently permitted to sell to China, by 50 to 150% as measured in tokens per second.<\/p>\n<p>Huawei expects AI chip revenue to reach roughly $12 billion in 2026, up from $7.5 billion in 2025.\u00a0Nvidia\u2019s share of the Chinese AI accelerator market has effectively collapsed to zero, a development that CEO Jensen Huang has described as a \u201chorrible outcome\u201d for the United States because it breaks the software dependency on Nvidia\u2019s CUDA ecosystem that took two decades to build.<\/p>\n<p>For China\u2019s highly commercialised AI market, which focuses on deploying applications to hundreds of millions of users rather than conducting frontier research, the ASIC approach makes particular sense. Inference, the process of running a trained model at scale, rewards the kind of narrow optimisation that custom silicon provides. Training new models still benefits from GPU flexibility, but the revenue is in deployment.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"The_software_stack_problem\"><\/span>The software stack problem<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Hardware performance is only half the equation.\u00a0The deeper challenge for China\u2019s chip industry\u00a0is breaking the lock-in created by Nvidia\u2019s CUDA platform, the software layer that millions of AI developers worldwide use to write code for Nvidia hardware. CUDA\u2019s network effects are enormous. Virtually every AI framework, every research paper, and every pre-trained model assumes CUDA compatibility.<\/p>\n<p>Huawei is building CANN as its alternative, while Moore Threads has developed MUSA. DeepSeek has spent months rewriting its core code to work with Huawei\u2019s CANN framework, moving away from the CUDA ecosystem. But semiconductor analyst Zhang Haijun notes that as AI models grow more complex, the boundaries between custom ASICs and flexible GPUs are \u201cbecoming increasingly blurry,\u201d suggesting that the winning architecture may eventually combine elements of both.<\/p>\n<p>Omdia chief analyst Su Lian Jye frames the choice practically: enterprises with robust AI engineering capabilities and a clear roadmap benefit from ASICs, while those running mixed workloads still lean toward general-purpose GPUs. For now, market momentum in China favours the specialist approach, partly by choice and partly because\u00a0the general-purpose option from Nvidia remains either unavailable or restricted.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"A_structurally_different_ecosystem\"><\/span>A structurally different ecosystem<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>The long-term consequence of this divergence may be more significant than the near-term performance benchmarks. If China\u2019s AI industry standardises on a mix of Huawei NPUs, Alibaba PPUs, and Cambricon domain-specific chips, each running its own software stack, the result will be a fragmented but domestically self-sufficient ecosystem that operates on fundamentally different architectural assumptions from the West.<\/p>\n<p>That fragmentation carries costs. Developers building for the Chinese market may need to support multiple hardware platforms simultaneously, increasing complexity. Cross-border AI collaboration becomes harder when the underlying compute stacks are incompatible. And the lack of a single dominant platform means no Chinese chip maker benefits from\u00a0the kind of ecosystem lock-in that made Nvidia\u2019s CUDA so powerful\u00a0in the first place.<\/p>\n<p>But the direction is set. US export controls intended to slow China\u2019s AI progress have instead accelerated a structural redesign of its chip industry, pushing it toward custom silicon, domestic software stacks, and an architecture that no longer depends on American hardware. Whether that ecosystem can match the pace of innovation in the Nvidia-powered West is the defining question of the AI chip race.<\/p>\n<\/p><\/div>\n<blockquote><p><strong><span style=\"color: #ff6600;\">If you liked the article, do not forget to share it with your friends. Follow us on\u00a0<span style=\"color: #ff0000;\"><a style=\"color: #ff0000;\" href=\"https:\/\/news.google.com\/publications\/CAAqBwgKMN63nwsw68G3Aw\" target=\"_blank\" rel=\"nofollow noopener noreferrer\">Google News<\/a><\/span>\u00a0too, click on the star and choose us from your favorites.<\/span><\/strong><\/p><\/blockquote>\n<blockquote>\n<p style=\"text-align: center;\"><strong>If you want to read more like this article, you can visit our <span style=\"color: #ff9900;\"><a style=\"color: #ff9900;\" href=\"https:\/\/buradabiliyorum.com\/en\/category\/technology\/\" target=\"_blank\" >Technology category.<\/a><\/span><\/strong><\/p>\n<\/blockquote>\n<p><span style=\"color: black;\"><a style=\"color: #ff9900;\" href=\"https:\/\/thenextweb.com\/news\/china-ai-chip-asic-gpu-nvidia-export-controls\" target=\"_blank\" >Source<\/a><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>TL;DR US export controls are pushing China\u2019s AI chip industry away from general-purpose GPUs and toward custom ASICs. Huawei leads with 62% projected market share, while Alibaba and Cambricon pursue alternative architectures that may create a structurally different ecosystem from the Nvidia-dominated West. China\u2019s AI chip industry is no longer trying to build an Nvidia&#8230;<\/p>\n","protected":false},"author":1,"featured_media":730824,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"fifu_image_url":"https:\/\/media.thenextweb.com\/2026\/06\/china-ai-chip-asic-gpu-nvidia-export-controls.avif","fifu_image_alt":"","footnotes":""},"categories":[18],"tags":[],"class_list":["post-730823","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-technology"],"_links":{"self":[{"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/posts\/730823","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/comments?post=730823"}],"version-history":[{"count":0,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/posts\/730823\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/media\/730824"}],"wp:attachment":[{"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/media?parent=730823"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/categories?post=730823"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/tags?post=730823"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}