Nvidia’s share of China’s market for data-centre AI chips fell to 34% in the first half of 2026, Reuters reported on 13 October 2026, citing an IDC report seen by Reuters. According to the IDC data, Nvidia shipped 678,000 AI accelerators in China from January through June, down 44% from a year earlier.
Huawei shipped 572,000 AI accelerators, up from more than 300,000 a year earlier, giving it a 28% share of the overall market, IDC said, according to Reuters.
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The key insight: As we read it, the chip that wins China is changing as well as the vendor: IDC says other AI accelerators, a category that includes chips for running trained models, overtook GPUs by volume in the first half of 2026, while Nvidia’s share fell to 34%.
Reuters reports that total AI-accelerator shipments in China reached 2.008 million units in the first half. Shipments of graphics processing units, the chips most widely used to train AI models, fell 26% to 991,000 units, as supplies eligible for sale in mainland China remained limited, IDC said.
Shipments of other AI accelerators rose nearly 80% to 1.016 million units, overtaking GPUs by volume, according to the report. Reuters says this category includes chips designed for specific AI tasks, such as running trained models.
After Nvidia and Huawei, IDC put Alibaba’s chip-design unit T-Head at 7%, Cambricon at 5%, Baidu’s Kunlunxin at 4% and Hygon at 3%, Reuters reports. Nine of the 11 Chinese chipmakers tracked by IDC increased shipments from a year earlier.
Share of China’s data-centre AI-accelerator market in the first half of 2026, from IDC data reported by Reuters on 13 October 2026: Nvidia 34%, Huawei 28%, Alibaba’s T-Head 7%, Cambricon 5%, Baidu’s Kunlunxin 4%, Hygon 3%.
Why Nvidia’s Share Shrank
Reuters attributes the fall to US export controls that restricted supplies of Nvidia’s products, and to domestic rivals led by Huawei gaining ground. It notes that Washington has restricted China’s access to Nvidia’s most powerful AI chips, while Beijing has promoted domestic alternatives and required Chinese companies to seek approval to import compliant Nvidia chips.
Reuters also reports that Nvidia CEO Jensen Huang has repeatedly criticised the export curbs, saying the policy forced a US company to cede China’s $50 billion AI chip market to Huawei. We covered his earlier argument that export controls have largely backfired. Nvidia did not respond to Reuters’ request for comment.
From Single Chips to Systems
IDC said competition was shifting from the performance of a single chip to system-level capabilities, including how well chips work in a larger computing cluster, according to Reuters.
Huawei, T-Head, Kunlunxin and Cambricon together accounted for 95% of the non-GPU segment, which IDC said was being adopted by government agencies, internet companies and telecoms providers. Huawei’s own 2027 chip roadmap leads with the network rather than the die, and its Ascend line faces a memory constraint, as we have reported.
IDC expects total accelerator shipments in China to grow 19% this year, even as GPU shipments fall 9%, Reuters reports.
The Structural Read
As we read it, the share loss is partly a supply limit: Reuters reports that US export controls restricted supplies of Nvidia’s products, and IDC said GPU supplies eligible for sale in mainland China remained limited.
As we read it, the gap is closing from the domestic side too: IDC data shows Huawei shipped 572,000 accelerators, up from more than 300,000, and nine of the 11 Chinese chipmakers it tracks increased shipments.
As we read it, the contest is moving to the cluster: IDC said competition is shifting from the performance of a single chip to how well chips work in a larger computing cluster.
IDC, as reported by Reuters, 13 October 2026
“IDC expects total accelerator shipments in China to grow 19% this year, even as GPU shipments fall 9%.”
Three Implications
NVIDIA IDC data reported by Reuters puts its China share at 34% and its H1 shipments at 678,000, down 44%; IDC did not say which Nvidia products the figure covers.
CHINESE CHIPMAKERS Huawei, T-Head, Kunlunxin and Cambricon accounted for 95% of the non-GPU segment, which IDC said government agencies, internet companies and telecoms providers are adopting.
AI BUYERS IN CHINA IDC expects total accelerator shipments to grow 19% this year while GPU shipments fall 9%, according to Reuters.
The framework puts it this way: “Training builds the brain. Inference is the brain working.”
As we read it, IDC’s China data fits that split: the category that includes chips for running trained models grew nearly 80% and overtook GPUs by volume, while GPU shipments fell 26%.
IDC data as reported by Reuters on 13 October 2026: China’s AI-accelerator shipments in the first half of 2026 reached 2.008 million units. Other AI accelerators rose nearly 80% to 1.016 million, overtaking GPUs, which fell 26% to 991,000.
What Is Not Established
The IDC report is not public; every figure here is as Reuters reported it. IDC did not specify which Nvidia products made up its 34% share, or whether the figure included chips such as the B200 and B300, which Reuters says are barred from export to China but have been smuggled into the country. The figures are unit shipments, not revenue, and IDC’s full-year growth figures are a forecast.
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On IDC’s data as reported by Reuters, Nvidia’s share of China’s data-centre AI chips fell to 34% in the first half of 2026 as its shipments dropped 44% to 678,000, while Huawei shipped 572,000 for a 28% share and non-GPU accelerators overtook GPUs by volume.
A note on sourcing. This piece is based on Reuters’ report of 13 October 2026, which we read in full on the same day. The IDC report Reuters cites is not public, so every figure here is as Reuters reported it. The shares are of unit shipments, not revenue, and IDC’s full-year figures are a forecast. Nothing here is investment advice.
Gennaro Cuofano is a CRO and tech executive who has worked in AI since late 2015, starting with bringing NLP, natural-language generation, voice and chatbot products to the marketing industry. His background is in law and finance: he holds a Master's degree in Law and an International MBA with an emphasis on corporate finance (LUISS Business School and the University of San Diego, 2012), and worked as a financial analyst at a real-estate investment firm in San Diego and as an assistant controller. His work focuses on business model strategy, business engineering and, more broadly, structural analysis: how companies make money, read from their own filings. He created FourWeekMBA and leads research there and at The Business Engineer, his newsletter on AI and business strategy, with over 95,000 subscribers and more than 1,000 published analyses. His writing has also appeared on Entrepreneur, HackerNoon and Search Engine People. Find him on LinkedIn and Substack. See how we source.
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