--- title: "NVIDIA tops the data center Ethernet rankings: Investment revelations indicate that the computing power frenzy is far from over, and GPUs no longer dominate the AI bull market" type: "News" locale: "en" url: "https://longbridge.com/en/news/290195362.md" description: "The IDC report shows that NVIDIA has become the number one in global data center Ethernet switch market revenue for the first time. This marks that the demand for AI computing power has expanded from GPUs to the entire industrial chain, including network infrastructure. Institutions such as Morgan Stanley have raised their capital expenditure expectations for American tech giants for 2026-2027, indicating that the AI computing power arms race has entered a stage of system-level expansion, with related infrastructure investments continuing to surge" datetime: "2026-06-18T12:59:02.000Z" locales: - [zh-CN](https://longbridge.com/zh-CN/news/290195362.md) - [en](https://longbridge.com/en/news/290195362.md) - [zh-HK](https://longbridge.com/zh-HK/news/290195362.md) --- # NVIDIA tops the data center Ethernet rankings: Investment revelations indicate that the computing power frenzy is far from over, and GPUs no longer dominate the AI bull market According to the latest research report released by the globally renowned research institution IDC, the world's highest market capitalization company—**the AI chip superpower NVIDIA (NVDA.US) has become the largest supplier in the global data center Ethernet switch market based on revenue for the first time.** According to IDC's "Quarterly Ethernet Switch Tracker," the global Ethernet switch market size surged by 39.8% year-on-year in the first quarter of 2026, reaching $15.4 billion. **IDC's latest report aligns with the views of Wall Street giants such as Morgan Stanley, Goldman Sachs, and Bank of America, indicating that leaders in the AI computing power industry chain, like NVIDIA, are advancing the coverage of the computing power chain from "GPU/AI chip single-point control" to a system-level closed loop of AI factory systems, including "GPU clusters + networks + DPUs + optical interconnect systems + software ecosystems."** The research institution pointed out in the report that as the global AI computing power infrastructure construction progresses rapidly, the complete set of AI computing power demand associated with AI data center delivery has collectively surged, especially in the segmented market covering high-speed switch infrastructure systems within large-scale cloud computing and enterprise data centers. **Driven by the massive AI inference and training workload investments, this segment has skyrocketed by 61% year-on-year, reaching $10 billion, occupying a significant portion of the $15.4 billion market size.** Morgan Stanley stated that the AI computing power arms race has entered a system-level expansion phase, with the institution significantly raising its capital expenditure expectations for major U.S. tech giants in 2026 from $433 billion a year ago to $805 billion, and capital expenditures in 2027 are expected to reach $1.1 trillion, up from the previous forecast of $950 billion. **Morgan Stanley's latest expectations highlight that the supply chain bottlenecks in AI computing power infrastructure have expanded from "large-scale purchases of GPUs/ASICs" to "striving to simultaneously address the entire delivery process of AI data centers, including data center power equipment, liquid cooling, data center CPUs, DRAM/NAND/HBM, data center optical communication/optical interconnect, high-performance Ethernet network infrastructure, transformers, gas turbines, etc."** According to IDC's segmented calculation data, in the first quarter of 2026, the total revenue of Ethernet switches for ordinary enterprise-level campuses and branch offices grew by 12.3% year-on-year, reaching $5.4 billion. In a milestone transformation, **NVIDIA has become the largest supplier in the data center Ethernet switch market based on total revenue for the first time. IDC added that supported by hardware upgrade cycles and rising prices of related components, the campus and branch office switch business grew by 12.3% year-on-year.** IDC data shows that \*\*with a year-on-year growth of 192.7% and $2.1 billion in the latest quarterly revenue, NVIDIA's Spectrum-X platform has captured the strong demand from large-scale cloud vendors and large enterprises for AI factory-type network infrastructure through the integrated collaborative design of AI GPU computing clusters and network infrastructure. The research institution pointed out that this structural transformation is reshaping the vendor rankings in the data center network industry \*\* According to IDC, NVIDIA became the largest supplier in the data center Ethernet switch market in the first quarter of 2026, marking a transformation in data center networks and reflecting the increasing influence of the latest AI computing power infrastructure clusters on procurement decisions. Buyers focusing on AI factory-type campuses have begun to factor in the impact of the ongoing rise in Average Selling Price (ASP) when planning budget updates. "NVIDIA's rise to the top of the data center Ethernet switch market in just one year is one of the most significant supplier landscape changes tracked by IDC in the enterprise networking space. The Spectrum-X-led AI GPU and network infrastructure integrated design is winning many AI factory deals, which existing network suppliers cannot compete with solely on independent hardware. The campus side tells a different but equally important story: the wave of Ethernet network infrastructure upgrades is real, but once memory supply constraints ease, IT teams should plan for ASP normalization. Budgeting for this transition now, rather than waiting for price changes, is essential," said Paul Nicholson, Vice President of Cloud and Data Center Network Research at IDC. It is understood that while the core function of switches relies on "Switch Chips" for fast packet forwarding, switches would be completely non-functional without storage chips providing software guidance, configuration storage, address resolution, and data buffering workloads in the background. Buffer memory is typically the most critical storage determining switch performance, usually extremely high-speed SRAM or DRAM. IDC pointed out that **massive AI inference computing power deployments are accelerating among hyperscale cloud vendors and large organizations, primarily used to enhance customer experience, reduce operational risks, and empower key business areas including IT infrastructure and operations, software development, and sales. According to IDC's report, the widespread adoption of AI workloads from large-scale training clusters to enterprise edge inference is driving the ongoing demand for high-speed, low-latency data center network infrastructure**. ## Spectrum-X completely rewrites the landscape of data center network infrastructure, extending the "AI computing power arms race narrative" from GPUs to switches and many other computing power fields IDC expects that driven by the continued massive investments in AI computing power infrastructure by hyperscale cloud vendors and enterprises, the Ethernet switch market will maintain strong growth momentum in 2026. The research institution stated that as inference deployments expand alongside training workloads, the strong demand for high-speed data center switching, particularly for rates of 800G and above, is expected to remain robust. IDC added that NVIDIA's position will face increasing competitive responses from long-established Ethernet ecosystem suppliers such as Cisco, Arista, and Broadcom, making the data center segment one of the most active competitive segments in the networking field. IDC stated that in the campus and branch areas, the upgrade cycle is expected to continue strongly, but if memory/storage chip supply constraints significantly ease and weaken the favorable ASP pricing, overall revenue growth may slow IDC also pointed out that significant uncertainties at the macroeconomic level, particularly including tariff risks and regional economic fluctuations, remain factors that need close attention and may suppress investment decisions in certain regions. **The following is IDC's latest compilation of the competitive landscape of the global data center Ethernet switch market:** **NVIDIA (NVDA.US)** IDC stated that all of NVIDIA's Ethernet switch revenue comes from the data center segment, with a staggering year-on-year increase of 192.7% in the first quarter of 2026, reaching $2.1 billion, giving it a 21.5% share in the data center segment. The company's exclusively developed Spectrum-X high-performance Ethernet platform is an end-to-end AI data center high-performance network solution that combines Spectrum Ethernet switches with BlueField DPU and NVIDIA LinkX cabling systems, specifically designed for NVIDIA's large-scale AI GPU computing clusters. It has become the preferred network interconnect solution for large-scale AI training and inference clusters, gaining significant configuration appeal among hyperscale cloud computing vendors and AI-native cloud service providers leading the construction of AI factories. **Arista Networks (ANET.US)** 92% of Arista's Ethernet switch revenue comes from the data center segment, with its high-performance Ethernet-related business revenue in the first quarter of 2026 increasing by 37.3% year-on-year to $2.2 billion. In contrast, NVIDIA's single Ethernet switch revenue is comparable to Arista's total Ethernet revenue. Although Arista's total Ethernet switch revenue of approximately $2.2 billion is slightly higher than NVIDIA's, 92% of it comes from data centers, which is about $2.02 billion in data center Ethernet-related revenue. According to IDC, Arista holds a 14.6% share in the overall Ethernet switch market and a 20.7% share in the data center segment, maintaining a strong growth position in 400G and 800G deployments aimed at hyperscale cloud customers. **Cisco (CSCO.US)** IDC reported that Cisco's total revenue related to Ethernet switches increased by 24% year-on-year in the first quarter of 2026, capturing a 29.3% market share. Non-data center revenue accounted for 60.5% of Cisco's total revenue, growing by 14.1% year-on-year, reflecting a favorable upgrade of network infrastructure in data center campuses; meanwhile, data center-related revenue surged by 43% year-on-year, driven by strong demand for AI computing infrastructure. According to IDC, Cisco's total revenue related to routers increased by 24.4% year-on-year in the first quarter of 2026, giving the company a market share of up to 35.1%. **Hewlett Packard Enterprise (HPE.US)** IDC noted that 70.5% of Hewlett Packard Enterprise's total Ethernet switch revenue comes from non-data center segments, with the company's total Ethernet switch revenue in the first quarter of 2026 increasing by 15.4% year-on-year, achieving a market share of 6.4% After completing all acquisition matters in July 2025, the total revenue data of Huiyu Technology now includes Juniper Networks. According to IDC statistics, the company's deepened campus and branch product portfolio system is transforming the current wave of upgrades into strong revenue. **Huawei** According to the latest IDC statistics, Chinese tech giant Huawei's total revenue associated with Ethernet switches in the first quarter of 2026 saw a significant year-on-year increase of 27.2%, reaching $895 million, giving the company a market share of 5.8%. IDC noted that Huawei's revenue related to routers grew by 0.8% year-on-year in the first quarter of 2026, with a market share of approximately 25.4%, highlighting its continued strong strength in the service provider network segment, especially in China and some emerging markets. ## From GPU to Ethernet Switches, the AI Factory Construction Process is in Full Swing: Under Goldman Sachs' Heavy Asset AI Infrastructure Logic, the Bull Market for Computing Power Chains is Far from Over As shown in the IDC research report, leaders in the AI computing power industry chain, such as NVIDIA, are advancing the coverage of the computing power chain from "single-point control of GPU/AI chips" to an AI factory system-level closed loop involving "GPU + network + DPU + optical interconnect systems + software." **The bottleneck for AI training and inference clusters is no longer just about "how many GPUs to buy," but whether GPUs can synchronize, transmit parameters, schedule inferences, and isolate multi-tenants through low-latency, high-bandwidth, low-loss, and high-utilization networks.** In other words, **NVIDIA's dominance in the data center Ethernet switch market proves that the "demand frenzy for computing power chains" has expanded from AI GPU and AI ASIC/TPU computing clusters to the entire AI computing power chain, including HBM, advanced packaging systems, high-performance Ethernet network infrastructure, optical interconnect systems, DPU, data center cables, ABF/glass substrates, switch chips, and even gas turbines and power management systems.** Goldman Sachs recently released a research report indicating that AI CapEx (capital expenditures related to AI) is no longer concentrated on large-scale purchases of NVIDIA Blackwell/Rubin AI GPU computing clusters, **but covers the entire AI factory chain, including data center power equipment, liquid cooling, data center CPUs, DRAM/NAND/HBM, optical communication/optical interconnect, high-performance Ethernet network infrastructure/data center DCI high-speed interconnect, transformers, gas turbines, and more. NVIDIA CEO Jensen Huang stated on Wednesday that artificial intelligence has the potential to usher in a new era of growth for American manufacturing and industry.** Goldman Sachs' benchmark framework estimates that investments by hyperscale cloud computing vendors are expected to reach $770 billion in 2026, close to their entire operating cash flow, predicting cumulative capital expenditures for AI infrastructure of approximately $7.6 trillion from 2026 to 2031, with annual AI CapEx in 2026 estimated at least around $765 billion, rising to about $1.6 trillion by 2031. In the view of Goldman Sachs' analyst team, the capital market pricing logic of the AI wave is shifting from "who can write the strongest AI large model/AI application software" to "who can quickly build AI computing clusters, achieve large-scale power supply, large-scale cooling, accelerate the advancement of optical interconnect within data centers and DCI interconnect between data centers, and continuously iterate the next generation of AI factories." According to Wall Street financial giant Goldman Sachs, the global bull market surrounding the AI computing power chain is far from over. The market's main narrative has upgraded from the long-standing "programming/code-driven software light asset valuation expansion" since 2008 to "repricing of AI computing infrastructure around a series of physical assets." **Goldman Sachs' latest judgment indicates that the next round of excess alpha returns will no longer be limited to the strongest leaders in the AI GPU/AI ASIC fields but will systematically spread to the full-stack AI computing infrastructure layer, including high-performance CPUs in data centers, DRAM/NAND/HBM storage, AI PCBs, liquid cooling systems, data center optical interconnect systems, ABF substrates/glass substrates, MLCCs, electronic fabrics, and extensive wafer foundries.** ![image.png](https://imageproxy.pbkrs.com/https://img.zhitongcaijing.com/image/20260618/1781783973714584.png?x-oss-process=image/auto-orient,1/interlace,1/resize,w_1440,h_1440/quality,q_95/format,jpg) Among Wall Street analysts, MarketBeat shows that 54 senior analysts have an average 12-month target price for NVIDIA of $305.67, with a highest target price of $500; TipRanks shows that 37 senior analysts have an average target price of $311.41, with a highest of $500; Investing.com shows that 59 analysts have an average target price of $298.93, with a highest of $500. The average target price of $305.67 corresponds to a market capitalization of approximately $7.43 trillion; if estimated at the highest target price of $500, it corresponds to a market capitalization of approximately $12.15 trillion. In contrast, NVIDIA traded around $207 in pre-market on Thursday, with a market capitalization hovering around $4.95 trillion ### Related Stocks - [NVDA.US](https://longbridge.com/en/quote/NVDA.US.md) - [NVDY.US](https://longbridge.com/en/quote/NVDY.US.md) - [NVDQ.US](https://longbridge.com/en/quote/NVDQ.US.md) - [NVDX.US](https://longbridge.com/en/quote/NVDX.US.md) - [NVDL.US](https://longbridge.com/en/quote/NVDL.US.md) - [NVD.US](https://longbridge.com/en/quote/NVD.US.md) - [07388.HK](https://longbridge.com/en/quote/07388.HK.md) - [NVDB.US](https://longbridge.com/en/quote/NVDB.US.md) - [07788.HK](https://longbridge.com/en/quote/07788.HK.md) - [NVDU.US](https://longbridge.com/en/quote/NVDU.US.md) - [NVDS.US](https://longbridge.com/en/quote/NVDS.US.md) - [NVDD.US](https://longbridge.com/en/quote/NVDD.US.md) - [NVDG.US](https://longbridge.com/en/quote/NVDG.US.md) - [NVDO.US](https://longbridge.com/en/quote/NVDO.US.md) - [NVDW.US](https://longbridge.com/en/quote/NVDW.US.md) - [NVYY.US](https://longbridge.com/en/quote/NVYY.US.md) - [NYYY.US](https://longbridge.com/en/quote/NYYY.US.md) - [DIPS.US](https://longbridge.com/en/quote/DIPS.US.md) - [09388.HK](https://longbridge.com/en/quote/09388.HK.md) - [MAGX.US](https://longbridge.com/en/quote/MAGX.US.md) - [SMH.US](https://longbridge.com/en/quote/SMH.US.md) - [SOXX.US](https://longbridge.com/en/quote/SOXX.US.md) - [SOXL.US](https://longbridge.com/en/quote/SOXL.US.md) - [SOXQ.US](https://longbridge.com/en/quote/SOXQ.US.md) - [XSD.US](https://longbridge.com/en/quote/XSD.US.md) - [PSI.US](https://longbridge.com/en/quote/PSI.US.md) - [FTXL.US](https://longbridge.com/en/quote/FTXL.US.md) - [MS.US](https://longbridge.com/en/quote/MS.US.md) - [GS.US](https://longbridge.com/en/quote/GS.US.md) - [BAC.US](https://longbridge.com/en/quote/BAC.US.md) - [CSCO.US](https://longbridge.com/en/quote/CSCO.US.md) - [ANET.US](https://longbridge.com/en/quote/ANET.US.md) - [AVGO.US](https://longbridge.com/en/quote/AVGO.US.md) - [HPE.US](https://longbridge.com/en/quote/HPE.US.md) - [JNPR.US](https://longbridge.com/en/quote/JNPR.US.md) - [NVD.DE](https://longbridge.com/en/quote/NVD.DE.md) - [MS-O.US](https://longbridge.com/en/quote/MS-O.US.md) - [MS-Q.US](https://longbridge.com/en/quote/MS-Q.US.md) - [MS-E.US](https://longbridge.com/en/quote/MS-E.US.md) - [MS-I.US](https://longbridge.com/en/quote/MS-I.US.md) - [MS-L.US](https://longbridge.com/en/quote/MS-L.US.md) - [MS-P.US](https://longbridge.com/en/quote/MS-P.US.md) - [MS-A.US](https://longbridge.com/en/quote/MS-A.US.md) - [MS-F.US](https://longbridge.com/en/quote/MS-F.US.md) - [MS-K.US](https://longbridge.com/en/quote/MS-K.US.md) - [W4VR.SG](https://longbridge.com/en/quote/W4VR.SG.md) - [BAC-Q.US](https://longbridge.com/en/quote/BAC-Q.US.md) - [BML-L.US](https://longbridge.com/en/quote/BML-L.US.md) - [BAC-L.US](https://longbridge.com/en/quote/BAC-L.US.md) - [BAC-K.US](https://longbridge.com/en/quote/BAC-K.US.md) - [BML-H.US](https://longbridge.com/en/quote/BML-H.US.md) - [BAC-N.US](https://longbridge.com/en/quote/BAC-N.US.md) - [BAC-E.US](https://longbridge.com/en/quote/BAC-E.US.md) - [MER-K.US](https://longbridge.com/en/quote/MER-K.US.md) - [BAC-O.US](https://longbridge.com/en/quote/BAC-O.US.md) - [BML-G.US](https://longbridge.com/en/quote/BML-G.US.md) - [BAC-M.US](https://longbridge.com/en/quote/BAC-M.US.md) - [BAC-B.US](https://longbridge.com/en/quote/BAC-B.US.md) - [BML-J.US](https://longbridge.com/en/quote/BML-J.US.md) - [BAC-S.US](https://longbridge.com/en/quote/BAC-S.US.md) - [BAC-P.US](https://longbridge.com/en/quote/BAC-P.US.md) - [8648.JP](https://longbridge.com/en/quote/8648.JP.md) - [HPE-C.US](https://longbridge.com/en/quote/HPE-C.US.md) ## Related News & Research - [SharonAI Raises $1.6 Billion to Expand NVIDIA AI Infrastructure](https://longbridge.com/en/news/290066574.md) - [Nvidia Supply Chain Gets A Boost As Coherent Expands Texas AI Manufacturing Facility](https://longbridge.com/en/news/290038332.md) - [Duos Technologies Secures Major GPU Financing for AI Expansion](https://longbridge.com/en/news/289471649.md) - [TD SYNNEX Expands HPE Unleash AI Solutions to Accelerate Partner Delivery of Enterprise AI Solutions | SNX Stock News](https://longbridge.com/en/news/289934628.md) - [Chip startup Tensordyne expects $200 million in orders for AI system to rival Nvidia](https://longbridge.com/en/news/289795764.md)