Following Foxconn’s substantial order for the assembly of NVIDIA’s GB200 AI servers, according to a report from Economic Daily News, Foxconn has now exclusively secured a major order for the NVLink Switch, a key component of the GB200 renowned for enhancing computing power. The volume of this order is estimated to be seven times that of the server cabinets. Not only is this a brand new order, but it also carries a significantly higher gross profit margin compared to server assembly, the report noted.

While Foxconn does not comment on orders and customers, industry sources cited by the same report highlight that NVLink is an exclusive NVIDIA technology consisting of two parts. The first is the bridge technology, which connects the central processing unit (CPU) with the AI chip (GPU). The second is the switch technology, which is crucial for interconnecting GPUs, enabling thousands of GPUs to combine in operation, thereby maximizing their collective computing power.

Industry sources cited by Economic Daily News have stated that the key feature of the GB200 is not just its significant computing power but also its high-speed transmission capabilities. NVLink is considered the magic ingredient for enhancing this computing power.

Reportedly, the primary reason Foxconn has secured the exclusive order for NVIDIA’s NVLink is due to their long-standing cooperation and mutual understanding. Foxconn has been a leading manufacturer for network communication equipment for years, making it a reasonable choice for NVIDIA to entrust with these orders.

Industry sources cited by the report further claim that as each server cabinet requires seven NVLinks, this new order means that for every GB200 server cabinet produced, Foxconn receives an order for seven NVLink switches. Given that the profit margin for switches is considerably higher than for server assembly, this order is expected to significantly boost Foxconn’s operations.

Per the report, the world’s top seven switch manufacturers, including Dell, HP, Cisco, Nokia, and Ericsson, are all clients of Foxconn. This has enabled Foxconn to secure over 75% of the global market share in switches, firmly establishing its leading position.

Regarding the AI server market, Foxconn’s Chairman Young Liu previously revealed that the GB200 is in high demand, and he anticipates that Foxconn’s market share in AI servers could reach 40% this year.

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(Photo credit: NVIDIA)

With the United States expected to further restrict China from acquiring advanced GAA (Gate-All-Around) chip architecture capabilities, coupled with reports of poor yield rates in Samsung’s 3nm GAA generation, the semiconductor industry sources cited in a report from Commercial Times state that TSMC’s 3nm FinFET process is enjoying dominance. Reportedly, due to the high demand and limited supply capacity, upstream IC design companies are beginning to report price hikes.

Seven global tech giants, including NVIDIA, AMD, Intel, Qualcomm, MediaTek, Apple, and Google, are set to gradually adopt TSMC’s 3nm process. As per the sources cited in the report from Commercial Times, Qualcomm’s Snapdragon 8 Gen 4, built using TSMC’s N3E process, has seen a price increase of 25% compared to the previous generation, potentially triggering a subsequent trend of price hikes.

Samsung was the first to commence mass production of 3nm chips using the GAA process in June 2022. However, the first-generation N3 node, SF3E, did not achieve significant success and was initially limited to cryptocurrency applications. Subsequently, the yield rate for its own Exynos 2500 chip also fell short of expectations.

Additionally, Google’s Tensor processors, which are manufactured by Samsung, still use Samsung’s 4nm process in their fourth generation. However, it is said in the report that the fifth generation will switch to TSMC’s 3nm process.

In the second half of the year, numerous AI products will be launched in the consumer market. Among the three major players in the mobile chip market, Qualcomm’s Snapdragon 8 Gen 4, MediaTek’s Dimensity 9400, and Apple’s A18 and M4 series will all be built using TSMC’s N3 family. Moreover, Google’s Tensor G5 will also compete in the market.

It is rumored that Qualcomm’s Snapdragon 8 Gen 4 has already initiated the first wave of price increases. The industry sources cited in the report claim that the procurement cost of mobile chips was already high, with last year’s flagship 8 Gen 3 costing around USD 200. This year’s flagship chip might exceed USD 250. Whether competitors will follow suit remains to be seen.

However, industry sources cited by the report also point out that the price increase is within a reasonable range. Compared to the 5nm process, the cost per wafer for the 3nm process is about 25% higher. This increase does not yet take into account overall wafer quantities and design architecture factors.

TSMC President C.C. Wei has also revealed that TSMC products are highly power-efficient and have better yield rates. When considering the cost per chip, TSMC is the most cost-effective.

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(Photo credit: TSMC)

According to a report from South China Morning Post, Wang Tao, Executive Director, Chairman of the ICT Infrastructure Managing Board at Huawei, recently stated at the World Semiconductor Conference and Nanjing International Semiconductor Expo that Huawei’s advanced Ascend 910B AI chip achieves an efficiency of up to 80% compared to NVIDIA’s A100 when training large-scale language models. In terms of specific test performance, it surpasses NVIDIA’s A100 AI GPU by 20%.

Reportedly, leading Chinese companies such as Tencent Holdings and Baidu have also purchased the Ascend 910B chip for conference tasks, indicating substantial market adoption of the chip and encroaching on NVIDIA’s AI chip market share.

Huawei’s self-developed AI chip, the Ascend 910B, adopts the advanced Da Vinci architecture and supports various AI computing tasks such as deep learning and inference. The chip boasts computing capabilities of up to 320 TFLOPS in half-precision (FP16) and 640 TOPS in integer precision (INT8), all while consuming 310W of power.

Reportedly, it’s expected that Chinese tech giants may now be considering a shift towards local AI products, which could pose a challenge to NVIDIA. Currently, China accounts for 17% of NVIDIA’s revenue in the 2024 fiscal year, making the competition in the Chinese market increasingly fierce for NVIDIA.

According to a previous report from Reuters, NVIDIA, in response to the US ban on high-end chips, provided three chips specifically for the Chinese market, with the H20 chip receiving significant attention.

Hence, there are reports of a price reduction for the H20 chip to stimulate demand and address the intense competition from Huawei in the Chinese market. It’s reported that the price of the H20 chip is over 10% lower than Huawei’s Ascend 910B chip. The chip is reportedly to be sold at approximately 100,000 yuan per unit, while Huawei 910B sold at over 120,000 yuan per unit.

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(Photo credit: Huawei)

The continuous increase in silicon content driven by AI servers, high-performance computing (HPC) applications, and the AI integration of high-end smartphones has led to a surge in demand for semiconductors. According to a report from the Economic Daily News, major companies such as Apple, Qualcomm, NVIDIA, and AMD are reportedly securing substantial production capacity for TSMC’s 3nm process family. This has resulted in a queue of clients stretching all the way to 2026.

TSMC has a consistent policy of not commenting on individual client information. Regarding whether the high demand for production capacity will lead to price increases to reflect its value, TSMC emphasizes that its pricing strategy is always strategically oriented rather than opportunistically driven. TSMC will continue to work closely with clients to provide value.

As per sources cited by the same report, TSMC is not a company that raises prices arbitrarily. Reflecting value does not equate directly to price increases, even though the company holds a leading edge in advanced process technology. There are various ways for TSMC to demonstrate value to its customers.

The members of TSMC’s 3nm family include N3, N3E, N3P, as well as N3X and N3A. As the existing N3 technology continues to be upgraded, N3E, which began mass production in the fourth quarter of last year, targets applications such as AI accelerators, high-end smartphones, and data centers. N3P is scheduled for mass production in the second half of this year and is expected to become mainstream for applications in mobile devices, consumer products, base stations, and networking through 2026. N3X and N3A are customized for high-performance computing and automotive clients.

Source: TSMC

Industry sources cited by Economic Daily News in the report believe that with clients rushing to book production capacity, TSMC’s 3nm family will continue to experience tight supply over the next two years. This does not yet include Intel’s outsourcing demand for CPUs.

Due to the fact that TSMC’s 3nm family production capacity has already been fully allocated by customers for this year and next, the company’s plan to triple the relevant capacity this year compared to last year is still insufficient. To ensure an uninterrupted supply for the next two years, TSMC has implemented several measures to expand its production capacity.

Previously, during an earnings call, the company announced that due to robust demand, its strategy includes converting some 5nm equipment to support 3nm production. Industry sources cited by the report also reveal that TSMC’s total 3nm family capacity is continuously increasing, with monthly production capacity expected to reach between 120,000 and 180,000 wafers.

Meanwhile, the sources cited by the Economic Daily News indicate that the main sources of orders for TSMC’s 3nm family include major clients such as Apple, Qualcomm, NVIDIA, and AMD. Apple is expected to launch the iPhone 16 series as early as September, which is anticipated to be the first iPhone with AI capabilities, potentially sparking a new wave of upgrades among Apple fans.

Source: TSMC

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(Photo credit: TSMC)

The New York Times reported on June 5th that the U.S. Department of Justice (DOJ) and the Federal Trade Commission (FTC) have reached an agreement, led by senior officials of both agencies, over the past week. The DOJ will investigate whether NVIDIA has violated antitrust laws, while the FTC will examine the conducts of OpenAI and Microsoft.

Reportedly, Jonathan Kanter, who is said to be the top antitrust official in the DOJ’s Antitrust Division, highlighted at an AI conference at Stanford University last week that AI’s reliance on massive amounts of data and computing power gives dominant companies a significant advantage. In a February interview, FTC Chair Lina Khan stated that the FTC aims to identify potential issues in the early stages of AI development.

As per Reuters’ report, Microsoft, OpenAI, NVIDIA, DOJ and FTC did not immediately respond to requests for comment outside regular business hours.

In a May interview with CNBC, Appian co-founder and CEO Matt Calkins stated that AI might not be a winner take all market. He suggested that if alliances could secure victory in the AI race, Google would already have won.

Per a report from Roll Call on May 15th, a bipartisan Senate AI working group led by Senate Majority Leader Chuck Schumer released an AI roadmap, calling for the federal government to invest at least USD 32 billion annually in non-defense-related AI systems.

In March, The Information reported that Microsoft does not want its hiring of Inflection AI’s two co-founders and the majority of its 70-member team to be perceived as an acquisition.

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(Photo credit: NVIDIA)