TSMC has acknowledged fundamental visibility limitations in its semiconductor supply chain, stating in its latest annual report that it "inherently lacks visibility regarding the downstream use or user of final products." This disclosure relates to an incident where 7 nm chips manufactured for Sophgo were later identified in Huawei's Ascend 910B/C AI accelerators, whose hardware is subject to US export restrictions. The contract foundry outlined its standard process: receiving GDS files through intermediaries, validating technical specifications, creating photomasks, and fabricating wafers without insight into end applications. Subsequent analysis revealed that those very chips matched Huawei's specifications, providing components for approximately one million dual‑chiplet AI accelerator units, with two million dies shipped to Huawei.

The report warns that compliance violations by supply‑chain partners, such as failing to secure proper import, export or re‑export permits, could trigger regulatory investigations and penalties, even when TSMC adheres to its established protocols. US already proposed a $1 billion fine for TSMC. This visibility gap just shows that challenges in semiconductor manufacturing, where complex distribution networks obscure the path between fabrication and deployment, are not easily overcome. Foundries are facing increasing pressure to enhance tracking capabilities despite the inherent limitations of the contract manufacturing model. US sanctions on Chinese companies are growing their walls even higher, and this could mean that sanction-abiding companies might avoid doing business with Chinese entities altogether to avoid getting fined.

Huawei announced its CloudMatrix 384 system super node, which the company touts as its own domestic alternative to NVIDIA's GB200 NVL72 system, with more overall system performance but worse per-chip performance and higher power consumption. While NVIDIA's GB200 NVL72 uses 36 Grace CPUs paired with 72 "Blackwell" GB200 GPUs, the Huawei CloudMatrix 384 system employs 384 Huawei Ascend 910C accelerators to beat NVIDIA's GB200 NVL72 system. It takes roughly five times more Ascend 910C accelerators to deliver nearly twice the GB200 NVL system performance, which is not good on per-accelerator bias, but excellent on per-system level of deployment. SemiAnalysis argues that Huawei is a generation behind in chip performance but ahead of NVIDIA in scale-up system design and deployment.

When you look at individual chips, NVIDIA's GB200 NVL72 clearly outshines Huawei's Ascend 910C, delivering over three times the BF16 performance (2,500 TeraFLOPS vs. 780 TeraFLOPS), more on‑chip memory (192 GB vs. 128 GB), and faster bandwidth (8 TB/s vs. 3.2 TB/s). In other words, NVIDIA has the raw power and efficiency advantage at the chip level. But flip the switch to the system level, and Huawei's CloudMatrix CM384 takes the lead. It cranks out 1.7× the overall PetaFLOPS, packs in 3.6× more total HBM capacity, and supports over five times the number of GPUs and the associated bandwidth of NVIDIA's NVL72 cluster. However, that scalability does come with a trade‑off, as Huawei's setup draws nearly four times more total power. A single GB200 NVL72 draws 145 kW of power, while a single Huawei CloudMatrix 384 draws ~560 kW. So, NVIDIA is your go-to if you need peak efficiency in a single GPU. If you're building a massive AI supercluster where total throughput and interconnect speed matter most, Huawei's solution actually makes a lot of sense. Thanks to its all-to-all topology, Huawei has delivered an AI training and inference system worth purchasing. When SMIC, the maker of Huawei's chips, gets to a more advanced manufacturing node, the efficiency of these systems will also increase.

TSMC is confronting a potential $1 billion-plus penalty from the US Commerce Department after inadvertently fabricating compute chiplets later integrated into Huawei's Ascend 910 AI processor. The fine, potentially reaching twice the value of unauthorized shipments, reflects the scale of components that circumvented export controls limiting Chinese access to advanced semiconductor technology. The regulatory breach originated in late 2023 when TSMC processed orders from Sophgo, a design partner of crypto-mining firm Bitmain. These chiplets, which are manufactured on advanced process nodes and contain tens of billions of transistors, were identified in TechInsights teardown analysis of Huawei Ascend 910 AI accelerator, revealing a supply chain vulnerability where TSMC lacked visibility into the components' end-use.

Upon discovery of the diversion, TSMC immediately halted Sophgo shipments and engaged in discussions with Commerce Department officials. By January, Sophgo had been added to the Entity List, limiting its access to US semiconductor technology. A Center for Strategic and International Studies report revealed that Huawei obtained approximately two million Ascend 910B logic dies through shell companies that misled TSMC. Huawei's preference for TSMC-made dies was due to manufacturing challenges in domestic chip production. This incident has forced TSMC to strengthen its customer vetting protocols, including terminating its relationship with Singapore-based PowerAIR following internal compliance reviews. The enforcement process typically begins with a proposed charging letter detailing violations and penalty calculations, followed by a 30-day response period. As Washington tightens restrictions on AI processor exports to Chinese entities, semiconductor manufacturers are under increased pressure to implement rigorous controls throughout multinational supply chains.

According to a recent Center for Strategic and International Studies report, Huawei got its hand on approximately two million Ascend 910B logic dies through shell companies that misled TSMC. This acquisition violates US export controls designed to restrict China's access to advanced semiconductor technology. The report details how Huawei leveraged intermediaries to procure chiplets for its AI accelerators before TSMC discovered the deception and halted shipments. These components are critical for Huawei's AI hardware roadmap, which progressed from the original Ascend 910 (manufactured by TSMC on N7+ until 2020) to the domestically produced Ascend 910B and 910C chips fabricated at SMIC using first and second-generation 7 nm-class technologies, respectively. Huawei reportedly wanted TSMC-made dies because of manufacturing challenges in domestic chip production. The Ascend 910B and 910C reportedly suffer from poor yields, with approximately 25% of units failing during the advanced packaging process that combines compute dies with HBM memory.

Despite these challenges, the performance gap with market-leading solutions still remains but has narrowed considerably, with the Ascend 910C reportedly delivering 60% of NVIDIA H100's performance. Huawei has executed a strategic stockpiling initiative, particularly for high-bandwidth memory components. The company likely acquired substantial HBM inventory between August and December 2024, when restrictions on advanced memory sales to China were announced but not yet implemented. The semiconductor supply chain breach shows that enforcing technology export controls is challenging, and third parties can still purchase silicon for restricted companies. While Huawei continues building AI infrastructure for both internal projects and external customers, manufacturing constraints may limit its ability to scale deployments against competitors with access to more advanced manufacturing processes. Perhaps a future domestic EUV-based silicon manufacturing flow will allow Huawei to gain access to more advanced domestic production, completely circumventing US-imposed restrictions.

Huawei Technologies reported a robust 22% year-over-year revenue increase for 2024, reaching 860 billion yuan ($118.27 billion), demonstrating remarkable resilience amid continued US-imposed trade restrictions. The Chinese tech giant's resurgence was primarily driven by its revitalized smartphone division, which captured 16% of China's domestic market share, overtaking Apple in regional sales. This achievement was notably accomplished by deploying domestically produced chipsets, marking a significant milestone for the company. In collaboration with Chinese SMIC, Huawei delivers in-house silicon solutions to integrate with HarmonyOS for complete vertical integration. The company's strategic diversification into automotive technology has emerged as a crucial growth vector, with its smart car solutions unit delivering autonomous driving software and specialized chips to Chinese EV manufacturers.

In parallel, Huawei's Ascend AI 910B/C platform recently announced compatibility with DeepSeek's R1 large language model and announced availability on Chinese AI cloud providers like SiliconFlow. Through a strategic partnership with AI infrastructure startup SiliconFlow, Huawei is enhancing its Ascend cloud service capabilities, further strengthening its competitive position in the global AI hardware market despite ongoing international trade challenges. Even if the company can't compete on performance versus the latest solutions from NVIDIA and AMD due to the lack of advanced manufacturing required for AI accelerators, it can compete on costs and deliver solutions that are typically much more competitive with the price/performance ratio. Huawei's Ascend AI solutions deliver modest performance. Still, the pricing makes AI model inference very cheap, with API costs of around one Yaun per million input tokens and four Yuan per one million output tokens on DeepSeek R1.

According to a recent Reuters report, TSMC has decided to cut off Chinese firm Sophgo following the discovery of TSMC-manufactured components in Huawei's advanced AI processor. The suspension came after technology research firm TechInsights identified a TSMC-manufactured chip within Huawei's Ascend 910B processor during a detailed analysis. This discovery raised significant concerns, as Huawei has been restricted from accessing such technology under US export controls since 2020. TSMC promptly notified US authorities upon learning of the situation and launched an internal investigation. While being sanctioned by the US, Huawei needed to use a proxy firm to get access to high-end silicon manufacturing to produce its Ascend accelerators.

Sophgo, which has ties to cryptocurrency mining equipment manufacturer Bitmain, strongly denies any business relationship with Huawei. The company states it has provided TSMC with a detailed investigation report asserting its compliance with all applicable laws, saying: "SOPHGO has never been engaged in any direct or indirect business relationship with Huawei. SOPHGO has been conducting business in strict compliance with applicable laws and regulations, including but not limited to all the applicable US national export control laws and regulations, and has never been in violation of any of such laws and regulations. SOPHGO has provided detailed investigation report to TSMC to prove that SOPHGO is not related to the Huawei investigation."

Huawei has reportedly started shipping its Ascend 910C accelerator—the company's domestic alternative to NVIDIA's H100 accelerator for AI training and inference. As the report from China South Morning Post notes, Huawei is shipping samples of its accelerator to large NVIDIA customers. This includes companies like Alibaba, Baidu, and Tencent, which have ordered massive amounts of NVIDIA accelerators. However, Huawei is on track to deliver 70,000 chips, potentially worth $2 billion. With NVIDIA working on a B20 accelerator SKU that complies with US government export regulations, the Huawei Ascend 910C accelerator could potentially outperform NVIDIA's B20 processor, per some analyst expectations.

If the Ascend 910C receives positive results from Chinese tech giants, it could be the start of Huawei's expansion into data center accelerators, once hindered by the company's ability to manufacture advanced chips. Now, with foundries like SMIC printing 7 nm designs and possibly 5 nm coming soon, Huawei will leverage this technology to satisfy the domestic demand for more AI processing power. Competing on a global scale, though, remains a challenge. Companies like NVIDIA, AMD, and Intel have access to advanced nodes, which gives their AI accelerators more efficiency and performance.

Alibaba's T-Head unit, responsible for the design and development of in-house IC design, has announced the first domestic SSD controller based on the PCIe 5.0 specification standard. Called the Zhenyue 510, the SSD controller is aimed at enterprise SSD offerings. Interestingly, the Zhenyue 510 is powered by T-Head's custom Xuantie C910 cores based on RISC-V instruction set architecture (ISA). Supporting the PCIe 5.0 standard for interfacing, the SSD controller uses DDR5 memory as a cache buffer. Regarding the performance, there are no official figures yet, but the company claims to have 30% lower input/output latencies compared to competing offerings. T-Head claims the SSD has an IO processing capability of "3400 Kilo IOs per second, a data bandwidth of 14 Gbytes/s, and an extremely high energy efficiency of 420 Kilo IO per second for every Watt".

This is an essential step towards Chinese self-sufficiency as T-Head has designed various ICs for processing different tasks. Still, now Alibaba's chip design unit has a domestic design for storage as well. Claiming low latency figures, the Zhenyue 510 is suitable for enterprise workloads like big data analysis, as well as AI inference/training systems workloads. The development of Zhenyue 510 started in 1H 2021, and it took the company more than two years to complete the design and validation of the chip to prepare it for deployment. This is the second Chinese-made SSD controller after Yingren Technology (InnoGrit) announced their chip in September.

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