T-Head

Headlines · 3

1. 5d
   China's non-GPU AI accelerator shipments overtake GPUs as big tech turns chip seller

   IDC data shows China's data center AI accelerator shipments reached 2.008 million units in the first half of 2026, with non-GPU accelerators at 1.016 million — surpassing GPUs for the first time. Nvidia remained No. 1 with 34% share but its shipments fell 44% year-on-year, narrowing its lead over Huawei's Ascend (28%) to 6 percentage points; Alibaba's T-Head (7%) and Baidu's Kunlunxin (4%) joined Huawei and Cambricon in accounting for about 95% of the non-GPU segment. The report argues that with model profits still elusive, full-stack vendors are monetizing their own silicon: Alibaba plans Q1 2027 mass production for Zhenwu V900 and Panjiu super-node servers carrying it, Baidu is spinning off Kunlunxin (reported to seek a ~$50 billion valuation), and Huawei is bundling Ascend super-nodes while opening up CANN.

   36氪 人工智能 · 🔥 0
2. 5d
   NVIDIA's China AI chip share falls to 34% as Huawei closes gap to 6 points

   According to IDC data cited by 36Kr, NVIDIA's share of China's data center AI chip market fell to 34% in the first half of 2026, with Huawei at 28% — a gap of 6 percentage points versus 31 a year earlier. NVIDIA shipped 678,000 AI accelerators in China from January to June, down 44% year on year, while Huawei shipped 572,000, nearly double its year-earlier total of more than 300,000; NVIDIA's CFO previously said it shipped no Hopper data center products to mainland China in the quarter and took a $4.5 billion inventory charge. Huawei's gains came despite supply constraints, with Ascend 910C yields and high-bandwidth memory supply still capping output, and China's accelerator mix shifted as non-GPU accelerators (1.016 million units, up nearly 80%) exceeded GPUs (991,000) for the first time.

   36氪 人工智能 · 🔥 0
3. 5d
   Dazhihui and Alibaba Cloud rebuild market-data software as an AI-native app

   A case study in TMTPost's Yunqi Strategy Reference describes how Dazhihui, a Chinese market-data software vendor founded in 2000, worked with Alibaba Cloud to rebuild its products as AI-native apps; talks ran through the summer of 2024 and the project started that October. The work covered four areas: reworking 20-plus years of market, financial and news data so it is unambiguous for agents rather than humans; an agent framework on Alibaba Cloud's FinXScope 2.0 with orchestration, tool-execution and security-sandbox layers, plus a six-category Skill system for quotes, stock screening, proprietary indicators, research notes, trading assistance and enterprise data queries; a four-layer memory system; and human-plus-model evaluation. The article says intent recognition that took about 10 seconds with a third-party full-size model fell to 2-3 seconds with a smaller model and to milliseconds after intent classification was trained into a 4B model, with different sizes of Qwen models matched to different scenarios and GPU, T-Head PPU and elastic compute plus on-site FDE delivery supporting the build.

   钛媒体 · 🔥 0

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