Analysis: Ethernet gains on InfiniBand in data center connectivity market; White Box/ODM vendors top choice for AI hyperscalers
Disclaimer: The author used Perplexity.ai for the research in this article.
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Introduction:
In 2023, InfiniBand held an ~80% share of the data center switch market. A little over two years later, Ethernet has overtaken it in data center switch and server port counts. Indeed, the demand for Ethernet-based interconnect technologies continues to strengthen, reflecting the market’s broader shift toward scalable, open, and cost-efficient data center fabrics.
According to Dell’Oro Group research published in July 2025, Ethernet is on track to overtake InfiniBand and establish itself as the primary fabric technology for large-scale data centers. The report projects cumulative data center switch revenue approaching $80 billion over the next five years, driven largely by AI infrastructure investments. Other analysts say Ethernet now represents a majority of AI‑back‑end switch ports, likely well above 50% and trending toward 70–80% as Ultra Ethernet / RoCE‑based fabrics (Remote Direct Memory Access/RDMA over Converged Ethernet) scale.
With Nvidia’s expanding influence across the data center ecosystem (via its Mellanox acquisition), Ethernet-based switching platforms are expected to maintain strong growth momentum through 2026 and the next investment cycle.
Dominant Ethernet speeds and PHY/PMD trends:
In 2026, the Ethernet portfolio spans multiple tiers of performance, with 100G, 200G, 400G, and 800G serving as the dominant server‑ and fabric‑facing speeds, while 1.6T begins to appear in early AI‑scale spine and inter‑cluster links.
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Server‑to‑leaf topology:
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100G and 200G remain prevalent for general‑purpose and mid‑tier AI inference workloads, often implemented over 100GBASE‑CR4 / 100GBASE‑FR / 100GBASE‑LR and their 200G counterparts (e.g., 200GBASE‑CR4 / 200GBASE‑FR4 / 200GBASE‑LR4) using 4‑lane PAM4 modulation.
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Many AI‑optimized racks are migrating to 400G server interfaces, typically using 400GBASE‑CR8 / 400GBASE‑FR8 / 400GBASE‑LR8 with 8‑lane 50 Gb/s PAM4 lanes, often via QSFP‑DD or OSFP form‑factors.
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Leaf‑to‑spine and spine‑to‑spine topology:
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400G continues as the workhorse for many brownfield and cost‑sensitive fabrics, while 800G is increasingly targeted for new AI and high‑growth pods, typically deployed as 800GBASE‑DR8 / 800GBASE‑FR8 / 800GBASE‑LR8 over 8‑lane 100 Gb/s PAM4 links.
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IEEE 802.3dj is progressing toward completion in 2026, standardizing 200 Gb/s per lane operation a
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For cloud‑resident (hyperscale) data centers, the Ethernet‑switch leadership is concentrated among a handful of vendors that supply high‑speed, high‑density leaf‑spine fabrics and AI‑optimized fabrics.
Core Ethernet‑switch leaders:
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NVIDIA (Spectrum‑X / Spectrum‑4)
NVIDIA has become a dominant force in cloud‑resident Ethernet, largely by bundling its Spectrum‑4 and Spectrum‑X Ethernet switches with H100/H200/Blackwell‑class GPU clusters. Spectrum‑X is specifically tuned for AI workloads, integrating with BlueField DPUs and offering congestion‑aware transport and in‑network collectives, which has helped NVIDIA surpass both Cisco and Arista in data‑center Ethernet revenue in 2025. -
Arista Networks
Arista remains a leading supplier of cloud‑native, high‑speed Ethernet to hyperscalers, with strong positions in 100G–800G leaf‑spine fabrics and its EOS‑based software stack. Arista has overtaken Cisco in high‑speed data‑center‑switch market share and continues to grow via AI‑cluster‑oriented features such as cluster‑load‑balancing and observability suites. -
Cisco Systems
Cisco maintains broad presence in cloud‑scale environments via Nexus 9000 / 7000 platforms and Silicon One‑based designs, particularly where customers want deep integration with routing, security, and multi‑cloud tooling. While its share in pure high‑speed data‑center switching has eroded versus Arista and NVIDIA, Cisco remains a major supplier to many large cloud providers and hybrid‑cloud operators.
Other notable players:
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HPE (including Aruba and Juniper post‑acquisition)
HPE and its Aruba‑branded switches are widely deployed in cloud‑adjacent and hybrid‑cloud environments, while the HPE‑Juniper combination (via the 2025 acquisition) strengthens its cloud‑native switching and security‑fabric portfolio. -
Huawei
Huawei supplies CloudEngine Ethernet switches into large‑scale cloud and telecom‑owned data centers, especially in regions where its end‑to‑end ecosystem (switching, optics, and management) is preferred. -
White‑box / ODM‑based vendors
Most hyperscalers also source Ethernet switches from ODMs (e.g., Quanta, Celestica, Inspur) running open‑source or custom NOS’ (SONiC, Cumulus‑style stacks), which can collectively represent a large share of cloud‑resident ports even if they are not branded like Cisco or Arista. White‑box / ODM‑based Ethernet switches hold a meaningful and growing share of the data‑center Ethernet market, though they still trail branded vendors in overall revenue. Estimates vary by source and definition. - ODM / white‑box share of the global data‑center Ethernet switch market is commonly estimated in the low‑ to mid‑20% range by revenue in 2024–2025, with some market trackers putting it around 20–25% of the data‑center Ethernet segment. Within hyperscale cloud‑provider data centers specifically, the share of white‑box / ODM‑sourced Ethernet switches is higher, often cited in the 30–40% range by port volume or deployment count, because large cloud operators heavily disaggregate hardware and run open‑source NOSes (e.g., SONiC‑style stacks).
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ODM‑direct sales into data centers grew over 150% year‑on‑year in 3Q25, according to IDC, signaling that white‑box share is expanding faster than the overall data‑center Ethernet switch market.
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Separate white‑box‑switch market studies project the global data‑center white‑box Ethernet switch market to reach roughly $3.2–3.5 billion in 2025, growing at a ~12–13% CAGR through 2030, which implies an increasing percentage of the broader Ethernet‑switch pie over time.
Ethernet vendor positioning table:
| Vendor | Key Ethernet positioning in cloud‑resident DCs | Typical speed range (cloud‑scale) |
|---|---|---|
| NVIDIA | AI‑optimized Spectrum‑X fabrics tightly coupled to GPU clusters | 200G/400G/800G, moving toward 1.6T |
| Arista | Cloud‑native, high‑density leaf‑spine with EOS | 100G–800G, strong 400G/800G share |
| Cisco | Broad Nexus/Silicon One portfolio, multi‑cloud integration | 100G–400G, some 800G |
| HPE / Juniper | Cloud‑native switching and security fabrics | 100G–400G, growing 800G |
| Huawei | Cost‑effective high‑throughput CloudEngine switches | 100G–400G, some 800G |
| White‑box ODMs | Disaggregated switches running SONiC‑style NOSes | 100G–400G, increasingly 800G |
Supercomputers and modern HPC clusters increasingly use high‑speed, low‑latency Ethernet as the primary interconnect, often replacing or coexisting with InfiniBand. The “type” of Ethernet used is defined by three layers: speed/lane rate, PHY/PMD/optics, and protocol enhancements tuned for HPC and AI. Slingshot, the proprietary Ethernet-based solution from HPE, commanded 48.1% of performance for the Top500 list in June 2025 and 46.3% in November 2025. On both of the lists, it provided interconnectivity for six of the top 10 – including the top three: El Capitan, Frontier, and Aurora.
HPC Speed and lane‑rate tiers:
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Mid‑tier HPC / legacy supercomputers:
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100G Ethernet (e.g., 100GBASE‑CR4/FR4/LR4) remains common for mid‑tier clusters and some scientific workloads, especially where cost and power are constrained.
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AI‑scale and next‑gen HPC:
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400G and 800G Ethernet (400GBASE‑DR4/FR4/LR4, 800GBASE‑DR8/FR8/LR8) are now the workhorses for GPU‑based supercomputers and large‑scale HPC fabrics.
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1.6T Ethernet (IEEE 802.3dj, 200 Gb/s per lane) is entering early deployment for spine‑to‑spine and inter‑cluster links in the largest AI‑scale “super‑factories.”
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In summary, NVIDIA and Arista are the most prominent Ethernet‑switch leaders specifically for AI‑driven, cloud‑resident data centers, with Cisco, HPE/Juniper, Huawei, and white‑box ODMs rounding out the ecosystem depending on region, workload, and procurement model. In hyperscale cloud‑provider data centers, ODMs hold a 30%-to-40% market share.
References:
Will AI clusters be interconnected via Infiniband or Ethernet: NVIDIA doesn’t care, but Broadcom sure does!
Big tech spending on AI data centers and infrastructure vs the fiber optic buildout during the dot-com boom (& bust)
Fiber Optic Boost: Corning and Meta in multiyear $6 billion deal to accelerate U.S data center buildout
AI Data Center Boom Carries Huge Default and Demand Risks
Markets and Markets: Global AI in Networks market worth $10.9 billion in 2024; projected to reach $46.8 billion by 2029
Using a distributed synchronized fabric for parallel computing workloads- Part I
Using a distributed synchronized fabric for parallel computing workloads- Part II
Huawei, Qualcomm, Samsung, and Ericsson Leading Patent Race in $15 Billion 5G Licensing Market
According to a new LexisNexis report, the 5G patent licensing market is now worth ~$15 billion a year. The report underscores that high-fidelity patent data has become a core business variable, with millions of dollars in annual licensing value potentially reallocated as courts, licensors, and implementers increasingly anchor negotiations, litigation strategy, and Fair, Reasonable, and Non-Discriminatory (FRAND) rate-setting on standards-essential patents (SEP) and portfolio analytics. As the 5G end point market scales out from smartphones into industrial IoT, automotive, healthcare, and other mission- and safety-critical infrastructure domains, SEPs are now a primary lever shaping competitive dynamics and value capture in global technology markets.
Lately, Ericsson CEO Börje Ekholm has been talking about humanoid robots and “physical AI” as future cellular connected objects. Others are forecasting the transformation of passive, data-collecting Internet of Things (IoT) devices into autonomous, intelligent agents that leverage 5G/6G networks, edge computing, and on-device neural processing.
The LexisNexis report extends their patent analysis to leadership across granted and in-force 5G SEP family declarations, value-adjusted portfolio strength indicators, and the depth and quality of technical contributions into the 3GPP work program.
Key findings from the 2026 analysis include:
- Huawei, Qualcomm, Samsung, and Ericsson continued to lead the global ranking of 5G patent powerhouses as assessed by granted and active 5G patent family volume, portfolio impact, and standards contributions.
- Patent data accuracy has a significant financial impact, as even small discrepancies in perceived portfolio share can translate into hundreds of millions of dollars in annual licensing value in a $15 billion global market.
- New entrants to the Top 50 list in 2026 include research-focused organizations, licensing and investment-led IP holders, and automotive and IoT connectivity specialists, which replaced several operator-centric and diversified industrial portfolios that fell below the Top 50 threshold.
- Top 50 5G patent owners reflected broad geographic diversity, with companies headquartered in China (14), Japan (9), the United States (9), Europe (7), Taiwan (5), South Korea (5), and Canada (1).
- Patent data is increasingly relied upon in FRAND determinations, making the quality, consistency, and verification of declaration data a critical factor for both licensors and implementers.
Top 10 5G Patent Leaders 2026:
The Top 10 ultimate patent owners based on granted and active 5G patent families, value-adjusted portfolio indicators, and sustained participation in 3GPP standards development.
“As 5G licensing moves deeper into industrial, automotive, and infrastructure markets, the financial stakes tied to patent data accuracy continue to rise,” said Tim Pohlmann, Director of SEP Analytics for LexisNexis Intellectual Property Solutions. “In a licensing environment of this scale, even small differences in how 5G patent portfolios are measured can materially influence negotiations. That is why verified, unbiased data has become essential, not only for understanding who leads the 5G patent race, but for supporting defensible, data-driven FRAND discussions.”
The 2026 analysis is grounded in the Cellular Verified initiative led by LexisNexis Intellectual Property Solutions. Through this initiative, LexisNexis compared public ETSI declaration data with internal records from 35 ETSI-declaring companies, applying rigorous matching, normalization, patent family expansion, and corporate-tree ownership analysis.
This validation process is designed to reduce bias introduced by differing declaration practices and to provide a more accurate and impartial representation of declared 5G patent portfolios, an increasingly critical requirement as rankings and portfolio assessments are used as economic and legal reference points in licensing and litigation contexts.
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Comment and Analysis:
Huawei’s #1 5G patent position, while significant on headline indicators, does not fully capture the nuances of 5G SEP strength and monetization potential. Portfolio experts consistently stress that patent quality and essentiality vary widely; not every declared SEP underpins a core feature, just as a car seat does not have the same system-critical role as the motor in the overall vehicle architecture.
Beyond raw declaration counts and 3GPP contribution volume, LexisNexis applies its Patent Asset Index methodology to weight portfolio value using factors such as citation impact and international coverage, a framework under which Qualcomm currently ranks first and Huawei second. This aligns with the industry view that some of the most fundamental 5G capabilities extend directly from 4G-era OFDM-based air-interface work, an area where Qualcomm consolidated a strong position with its roughly 600 million dollar acquisition of OFDM specialist Flarion in 2006.
On the licensing side, Qualcomm remains the most financially leveraged SEP holder in the current ranking peer group: its Qualcomm Technology Licensing (QTL) unit generated about 5.6 billion dollars in fiscal 2024 revenue, or roughly 14% of total sales, and delivered around 4 billion dollars in pre-tax earnings, close to 30% of company-wide profit. Huawei, by contrast, reported approximately 630 million dollars in patent licensing revenue for 2024, equivalent to around 0.5% of its overall turnover, and notes that its cumulative royalty outpayments are nearly triple the royalties it has collected to date. While Huawei’s licensing income has roughly doubled compared with its pre‑2020 baseline, the company still spends several times more on patents and R&D than it earns from licensing, reflecting its dual role as both major licensor and large-scale implementer across devices and networks.
Ericsson and Nokia sit between the two on monetization intensity: in 2024, Ericsson’s IPR licensing revenue was about 14 billion Swedish kronor (roughly 1.57 billion dollars), or around 6% of group sales, while Nokia’s licensing business generated approximately 1.9 billion euros (about 2.3 billion dollars), roughly 10% of its total revenue, with both vendors showing solid double‑digit percentage growth in licensing since 2019. The updated LexisNexis study also segments 5G SEP leadership by 3GPP release based on active and granted declared 5G patent families: for Release 15, characterized as the foundational 5G baseline, the top six are Huawei, Qualcomm, Samsung, Ericsson, ZTE, and Nokia, while for Release 18—framing the first wave of 5G‑Advanced—the leaders shift toward LG Electronics, ETRI Korea, Samsung, Oppo, Foxconn, and Huawei, with Nokia the highest-ranked European or US player at eighth.
Assuming the ecosystem avoids major standards fragmentation, current trajectories suggest that Huawei and Qualcomm are well placed to carry substantial 5G-era influence into 6G, which is increasingly positioned as an evolutionary extension of 5G that pushes OFDM-based radio technologies into higher frequency bands and more advanced use cases. Barring disruptive structural changes, future 3GPP plenary and working group meetings are therefore likely to remain populated by the same core SEP powerhouses that dominate today’s 5G landscape.
References:
https://www.lexisnexisip.com/resources/5g-patent-race-2026/
The full “Who Is Leading the 5G Patent Race 2026” analysis, including the Top 50 5G Patent Rankings 2026 and detailed information on the underlying data methodology and validation process, is available at www.LexisNexisIP.com/5G-Report-2026
https://www.lightreading.com/5g/huawei-and-qualcomm-tussle-for-5g-patents-lead-as-6g-draws-closer
Huawei’s Electric Vehicle Charging Technology & Top 10 Charging Trends
ABI Research: Telco transformation measured via patents and 3GPP contributions; 5G accelerating in China
Huawei or Samsung: Leader in 5G declared Standard Essential Patents (SEPs)?
5G Specifications (3GPP), 5G Radio Standard (IMT 2020) and Standard Essential Patents
GreyB study: Huawei undisputed leader in 5G Standard Essential Patents (SEPs)
Chinese companies’ patents awarded in the U.S. increased ~10% while U.S. patent grants declined ~7% in 2021
Samsung Partners with NEC and Qualcomm for 5G, Licenses Nokia Patents
Fiber Optic Boost: Corning and Meta in multiyear $6 billion deal to accelerate U.S data center buildout
Corning Incorporated and Meta Platforms, Inc. (previously known as Facebook) have entered a multiyear agreement valued at up to $6 billion. This strategic collaboration aims to accelerate the deployment of cutting-edge data center infrastructure within the U.S. to bolster Meta’s advanced applications, technologies, and ambitious artificial intelligence initiatives. The agreement specifies that Corning will furnish Meta with its latest advancements in optical fiber, cable, and comprehensive connectivity solutions. As part of this commitment, Corning plans to significantly scale its manufacturing capabilities across its North Carolina facilities.
A key element of this expansion is a substantial capacity increase at its fiber optic cable manufacturing plant in Hickory NC, for which Meta will serve as the foundational anchor customer. The construction and operation of these data centers — critical infrastructure that supports our technologies and moves us toward personalized superintelligence — necessitate robust server and hardware systems designed to facilitate information transfer and connectivity with minimal latency. Fiber optic cabling is a cornerstone component for enabling this high-speed, near real-time connectivity, powering applications from sophisticated wearable technology like the Ray-Ban Meta AI glasses to the global connectivity services utilized by billions of individuals and enterprises.
“This long-term partnership with Meta reflects Corning’s commitment to develop, innovate, and manufacture the critical technologies that power next-generation data centers here in the U.S.,” said Wendell P. Weeks, Chairman and Chief Executive Officer, Corning Incorporated. “The investment will expand our manufacturing footprint in North Carolina, support an increase in Corning’s employment levels in the state by 15 to 20 percent, and help sustain a highly skilled workforce of more than 5,000 — including the scientists, engineers, and production teams at two of the world’s largest optical fiber and cable manufacturing facilities. Together with Meta, we’re strengthening domestic supply chains and helping ensure that advanced data centers are built using U.S. innovation and advanced manufacturing.”
Meta is expanding its commitment to build industry-leading data centers in the U.S. and to source advanced technology made domestically. Here are two quotes from them:
- “Building the most advanced data centers in the U.S. requires world-class partners and American manufacturing,” said Joel Kaplan, Chief Global Affairs Officer at Meta. “We’re proud to partner with Corning – a company with deep expertise in optical connectivity and commitment to domestic manufacturing – for the high-performance fiber optic cables our AI infrastructure needs. This collaboration will help create good-paying, skilled U.S. jobs, strengthen local economies, and help secure the U.S. lead in the global AI race.”
- “As digital tools and generative AI continue to transform our economy — in fields like healthcare, finance, agriculture, and more — the demand for fiber connectivity will continue to grow. By supporting American companies like Corning and building and operating data centers in America, we’re helping ensure that our nation maintains its competitive edge in the digital economy and the global race for AI leadership.”
Key elements of the agreement:
- Multiyear, up to $6 billion commitment.
- Corning to supply latest generation optical fiber, cable and connectivity products designed to meet the density and scale demands of advanced AI data centers.
- New optical cable manufacturing facility in Hickory, North Carolina, in addition to expanded production capacity across Corning’s North Carolina operations.
- Agreement supports Corning’s projected employment growth in North Carolina by 15 to 20 percent, sustaining a skilled workforce of more than 5,000 employees in the state, including thousands of jobs tied to two of the world’s largest optical fiber and cable manufacturing facilities.
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Comment and Analysis:
Corning’s “up to $6 billion” Meta agreement is essentially a long‑term, anchor‑tenant bet that AI‑era data centers will be fundamentally more fiber‑intensive than legacy cloud resident data centers, with Corning positioning itself as the default U.S. optical plant for Meta’s buildout through ~2030. In practice, this deal is a long‑term take‑or‑pay style capacity lock that de‑risks Corning’s capex while giving Meta priority access to scarce, high‑performance data‑center‑grade fiber and cabling.
AI data centers are becoming the new FTTH in the sense that hyperscale AI buildouts are now the primary structural driver of incremental fiber demand, design innovation, and capex prioritization—but with far higher fiber intensity per site and far tighter performance constraints than residential access ever imposed.
Why “AI Data Centers are the new FTTH” for fiber optic vendors:
For fiber‑optic vendors, AI data centers now play the role that FTTH did in the 2005–2015 cycle: the anchor use case that justifies new glass, cable, and connectivity capacity.
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AI‑optimized data centers need 2–4× more fiber cabling than traditional hyperscalers, and in some designs more than 10×, driven by massively parallel GPU fabrics and east–west traffic.
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U.S. hyperscale capacity is expected to triple by 2029, forcing roughly a 2× increase in fiber route miles and a 2.3× increase in total fiber miles, a demand shock comparable to or larger than the early FTTH boom but concentrated in fewer, much larger customers.
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This is already reshaping product roadmaps toward ultra‑high‑fiber‑count (UHFC) cable, bend‑insensitive fiber, and very‑small‑form‑factor connectors to handle hundreds to thousands of fibers per rack and per duct.
In other words, where FTTH once dictated volume and economies of scale, AI data centers now dictate density, performance, and margin mix.
Carrier‑infrastructure: from access to fabric:
From a carrier perspective, the “new FTTH” analogy is about what drives long‑haul and metro planning: instead of last‑mile penetration, it’s AI fabric connectivity and east–west inter‑DC routes.
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Each new hyperscale/AI data center is modeled to require on the order of 135 new fiber route miles just to reach three core network interconnection points, plus additional miles for new long‑haul routes and capacity upgrades.
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An FBA‑commissioned study projects U.S. data centers alone will need on the order of 214 million additional fiber miles by 2029, nearly doubling the installed base from ~160M to ~373M fiber miles; that is the new “build everywhere” narrative operators once used for FTTH.
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Carriers now plan backbone routes, ILAs, and regional rings around dense clusters of AI campuses, treating them as primary traffic gravity wells rather than as just a handful of peering sites at the edge of a consumer broadband network.
The strategic shift: FTTH made the access network fiber‑rich; AI makes the entire cloud and transport fabric fiber‑hungry.
Strategic implications:
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AI is now the dominant incremental fiber use case: residential fiber adds subscribers; AI adds orders of magnitude more fibers per site and per route.
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Network economics are moving from passing more homes to feeding more GPUs: route miles, fiber counts, and connector density are being dimensioned to training clusters and inference fabrics, not household penetration curves.
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Policy and investment narratives should treat AI inter‑DC and campus fiber as “national infrastructure” on par with last‑mile FTTH, given the scale of projected doubling in route miles and more than doubling in fiber miles by 2029.
In summary, the next decade of fiber innovation and capex will be written less in curb‑side PON and more in ultra‑dense, AI‑centric data centers with internal fiber optical fabrics and interconnects.
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References:
Meta Announces Up to $6 Billion Agreement With Corning to Support US Manufacturing
Big tech spending on AI data centers and infrastructure vs the fiber optic buildout during the dot-com boom (& bust)
Analysis: Cisco, HPE/Juniper, and Nvidia network equipment for AI data centers
Networking chips and modules for AI data centers: Infiniband, Ultra Ethernet, Optical Connections
Will billions of dollars big tech is spending on Gen AI data centers produce a decent ROI?
Superclusters of Nvidia GPU/AI chips combined with end-to-end network platforms to create next generation data centers
Lumen Technologies to connect Prometheus Hyperscale’s energy efficient AI data centers
Proposed solutions to high energy consumption of Generative AI LLMs: optimized hardware, new algorithms, green data centers
Hyper Scale Mega Data Centers: Time is NOW for Fiber Optics to the Compute Server
China’s open source AI models to capture a larger share of 2026 global AI market
Overview of AI Models – China vs U.S. :
Chinese AI language models (LMs) have advanced rapidly and are now contesting with the U.S. for global market leadership. Alibaba’s Qwen-Image-2512 is emerging as a top-performing, free, open-source model capable of high-fidelity human, landscape, and text rendering. Other key, competitive models include Zhipu AI’s GLM-Image (trained on domestic chips), ByteDance’s Seedream 4.0, and UNIMO-G.
Today, Alibaba-backed Moonshot AI released an upgrade of its flagship AI model, heating up a domestic arms race ahead of an expected rollout by Chinese AI hotshot DeepSeek. The latest iteration of Moonshot’s Kimi can process text, images, and videos simultaneously from a single prompt, the company said in a statement, aligning with a trend toward so-called omni models pioneered by industry leaders like OpenAI and Alphabet Inc.’s Google.
Moonshot AI Kimi website. Photographer: Raul Ariano/Bloomberg
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Chinese AI models are rapidly narrowing the gap with Western counterparts in quality and accessibility. That shift is forcing U.S. AI leaders like Alphabet’s Google, Microsoft’s Copilot, OpenAI, and Anthropic to fight harder to maintain their technological lead in AI. That’s despite their humongous spending on AI data centers, related AI models and infrastructure.
In early 2025, investors seized on DeepSeek’s purportedly lean $5.6 million LM training bill as a sign that Nvidia’s high-end GPUs were already a relic and that U.S. hyperscalers had overspent on AI infrastructure. Instead, the opposite dynamic played out: as models became more capable and more efficient, usage exploded, proving out a classic Jevons’ Paradox and validating the massive data-center build-outs by Microsoft, Amazon, and Google.
The real competitive threat from DeepSeek and its peers is now coming from a different direction. Many Chinese foundation models are released as “open source” or “open weight” AI models which makes them effectively free to download, easy to modify, and cheap to run at scale. By contrast, most leading U.S. players keep tight control over their systems, restricting access to paid APIs and higher-priced subscriptions that protect margins but limit diffusion.
That strategic divergence is visible in how these systems are actually used. U.S. models such as Google’s Gemini, Anthropic’s Claude, and OpenAI’s GPT series still dominate frontier benchmarks [1′] and high‑stakes reasoning tasks. According to a recently published report by OpenRouter, a third-party AI model aggregator, and venture capital firm Andreessen Horowitz. Chinese open-source models have captured roughly 30% of the “working” AI market. They are especially strong in coding support and roleplay-style assistants—where developers and enterprises optimize for cost efficiency, local customization, and deployment freedom rather than raw leaderboard scores.
Note 1. A frontier benchmark for AI models is a high-difficulty evaluation designed to test the absolute limits of artificial intelligence in complex,, often unsolved, reasoning tasks. FrontierMath, for example, is a prominent benchmark focusing on expert-level mathematics, requiring AI to solve hundreds of unpublished problems that challenge, rather than merely measure, current capabilities.
China’s open playbook:
China’s more permissive stance on model weights is not just a pricing strategy — it’s an acceleration strategy. Opening weights turns the broader developer community into an extension of the R&D pipeline, allowing users to inspect internals, pressure‑test safety, and push incremental improvements upstream.
As Kyle Miller at Georgetown’s Center for Security and Emerging Technology argues, China is effectively trading away some proprietary control to gain speed and breadth: by letting capability diffuse across the ecosystem, it can partially offset the difficulty of going head‑to‑head with tightly controlled U.S. champions like OpenAI and Anthropic. That diffusion logic is particularly potent in a system where state planners, big tech platforms, and startups are all incentivized to show visible progress in AI.
Even so, the performance gap has not vanished. Estimates compiled by Epoch AI suggest that Chinese models, on average, trail leading U.S. releases by about seven months. The window briefly narrowed during DeepSeek’s R1 launch in early 2025, when it looked like Chinese labs might have structurally compressed the lag; since then, the gap has widened again as U.S. firms have pushed ahead at the frontier.
Capital, chips, and the power problem:
The reason the U.S. lead has held is massive AI infrastructure spending. Consensus forecasts put capital expenditure by largely American hyperscalers at roughly $400 billion in 2025 and more than $520 billion in 2026, according to Goldman Sachs Research. By comparison, UBS analysts estimate that China’s major internet platforms collectively spent only about $57 billion last year—a fraction of U.S. outlays, even if headline Chinese policy rhetoric around AI is more aggressive.
But sustaining that level of investment runs into a physical constraint that can’t be hand‑waved away: electricity. The newest data-center designs draw more than a gigawatt of power each—about the output of a nuclear reactor—turning grid capacity into a strategic bottleneck. China now generates more than twice as much power as the U.S., and its centralized planning system can more readily steer incremental capacity toward AI clusters than America’s fragmented, heavily regulated electricity market.
That asymmetry is already shaping how some on Wall Street frame the race. Christopher Woods, global head of equity strategy at Jefferies, recently reiterated that China’s combination of open‑source models and abundant cheap power makes it a structurally formidable AI competitor. In his view, the “DeepSeek moment” of early last year remains a warning that markets have largely chosen to ignore as they rotate back into U.S. AI mega‑caps.
A fragile U.S. AI advantage:
For now, U.S. companies still control the most important chokepoint in the stack: advanced AI accelerators. Access to Nvidia’s cutting‑edge GPUs remains a decisive advantage. Yesterday, Microsoft announced the Maia 200 chip – their first silicon and system platform optimized specifically for AI inference. The chip was was designed for efficiency, both in terms of its ability to deliver tokens per dollar and performance per watt of power used.
“Maia 200 can deliver 30% better performance per dollar than the latest generation hardware in our fleet today,” Microsoft EVP for Cloud and AI Scott Guthrie wrote in a blog post.
Image Credit: Microsoft
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Leading Chinese AI research labs have struggled to match training results using only domestic designed silicon. DeepSeek, which is developing the successor to its flagship model and is widely expected to release it around Lunar New Year, reportedly experimented with chips from Huawei and other local vendors before concluding that performance was inadequate and turning to Nvidia GPUs for at least part of the training run.
That reliance underscores the limits of China’s current self‑reliance push—but it also shouldn’t be comforting to U.S. strategists. Chinese firms are actively working around the hardware gap, not waiting for it to close. DeepSeek’s latest research focuses on training larger models with fewer chips through more efficient memory design, an incremental but important reminder that architectural innovation can partially offset disadvantages in raw compute.
From a technology‑editorial perspective, the underlying story is not simply “China versus the U.S.” at the model frontier. It is a clash between two AI industrial strategies: an American approach that concentrates capital, compute, and control in a handful of tightly integrated platforms, and a Chinese approach that leans on open weights, diffusion, and state‑backed infrastructure to pull the broader ecosystem forward.
The question for 2026 is whether U.S. AI firms’ lead in capability and chips can keep outrunning China’s advantages in openness and power—or whether the market will again wait for a shock like DeepSeek to re‑price that risk.
Deepseek and Other Chinese AI Models:
DeepSeek published research this month outlining a method of training larger models using fewer chips through a more efficient memory design. “We view DeepSeek’s architecture as a new, promising engineering solution that could enable continued model scaling without a proportional increase in GPU capacity,” wrote UBS analyst Timothy Arcuri.
Export controls haven’t prevented Chinese companies from training advanced models, but challenges emerge when the models are deployed at scale. Zhipu AI, which released its open-weight GLM 4.7 model in December, said this month it was rationing sales of its coding product to 20% of previous capacity after demand from users overwhelmed its servers.
Moonshot, Zhipu AI and MiniMax Group Inc are among a handful of AI LM front-runners in a hotly contested battle among Chinese large language model makers, which at one point was dubbed the “War of One Hundred Models.”
“I don’t see compute constraints limiting [Chinese companies’] ability to make models that are better and compete near the U.S. frontier,” Georgetown’s Miller says. “I would say compute constraints hit on the wider ecosystem level when it comes to deployment.”
Gaining access to Nvidia AI chips:
U.S. President Donald Trump’s plan to allow Nvidia to sell its H200 chips to China could be pivotal. Alibaba Group and ByteDance, TikTok’s parent company, have privately indicated interest in ordering more than 200,000 units each, Bloomberg reported. The H200 outperforms any Chinese-produced AI chip, with a roughly 32% processing-power advantage over Huawei’s Ascend 910C.
With access to Nvidia AI chips, Chinese labs could build AI-training supercomputers as capable as American ones at 50% extra cost compared with U.S.-made ones, according to the Institute for Progress. Subsidies by the Chinese government could cover that differential, leveling the playing field, the institute says.
Conclusions:
A combination of open-source innovation and loosened chip controls could create a cheaper, more capable Chinese AI ecosystem. The possibility is emerging just as OpenAI and Anthropic consider public stock listings (IPOs) and U.S. hyperscalers such as Microsoft and Meta Platforms face pressure to justify heavy spending.
The risk for U.S. AI leaders is no longer theoretical; China’s open‑weight, low‑cost model ecosystem is already eroding the moat that Google, OpenAI, and Anthropic thought they were building. By prioritizing diffusion over tight control, Chinese firms are seeding a broad developer base, compressing iteration cycles, and normalizing expectations that powerful models should be cheap—or effectively free—to adapt and deploy.
U.S. AI leaders could face pressure on pricing and profit margins from China AI competitors while having to deal with AI infrastructure costs and power constraints. Their AI advantage remains real, but fragile—highly exposed to regulatory shifts, export controls, and any breakthrough in China’s workarounds on hardware and training efficiency. The uncomfortable prospect for U.S. AI incumbents is that they could win the race for the best models and still lose ground in the market if China’s diffusion‑driven strategy defines how AI is actually consumed at scale.
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References:
https://www.barrons.com/articles/deepseek-ai-gemini-chatgpt-stocks-ccde892c
https://blogs.microsoft.com/blog/2026/01/26/maia-200-the-ai-accelerator-built-for-inference/
China gaining on U.S. in AI technology arms race- silicon, models and research
U.S. export controls on Nvidia H20 AI chips enables Huawei’s 910C GPU to be favored by AI tech giants in China
Goldman Sachs: Big 3 China telecom operators are the biggest beneficiaries of China’s AI boom via DeepSeek models; China Mobile’s ‘AI+NETWORK’ strategy
Bloomberg: China Lures Billionaires Into Race to Catch U.S. in AI
Comparing AI Native mode in 6G (IMT 2030) vs AI Overlay/Add-On status in 5G (IMT 2020)
Fierce Network Research report examines telcos role in the AI economy and profiles early AI adopters
The telecommunications industry is at a critical crossroads. As AI reshapes global value chains, communications service providers (CSPs) must determine their strategic position: will they remain infrastructure enablers or evolve into full-scale participants in the AI economy?
A new Fierce Network Research report — “Risk, Reward and Revenue: Defining Telcos’ Role in the AI Economy” — examines this identity challenge — and how network operators are recalibrating for the next generation of network-driven intelligence. Based on a global survey of 500 technology decision-makers across 40 countries, the findings reveal a pronounced industry divide. A majority (57%) of operators see their core opportunity in infrastructure — networks, data centers, and secure connectivity — while 43% advocate for a more integrated position, aspiring to orchestrate AI ecosystems (19%) or participate fully in the AI value chain (24%).
Some of the industry’s early adopters are already showing what that future might look like.
- AT&T reports a twofold increase in cash flow for every dollar it invests in AI, emphasizing measurable outcomes over vague productivity gains. An AT&T executive said that success in the AI era depends on “Goldilocks governance” — a balance not too rigid to stifle innovation, and not too loose to compromise compliance and trust.
- Bell Canada is moving in a similar direction, targeting a doubling of enterprise AI revenue by 2028 and positioning its Ateko subsidiary and AI Fabric platform as the backbone of a “sovereign digital spine” for Canada.
- “We’re using AI to enhance our products and services and make them better,” Ed Fox, MetTel CTO. The company provides a private network to deliver integrated communications and IT services to U.S. businesses and government agencies, including voice, data, network, cloud, mobility, IoT and security solutions. MetTel also provides managed network services such as SD-WAN and secure access service edge (SASE).
- Rick Lievano, Microsoft CTO for the worldwide telecommunications industry, sees operators expanding their use of AI beyond efficiency. “Initially, the first place where telcos began to experiment with AI is around efficiency gains — how can I save money, and how can I do more with fewer people? That’s been the target of the first couple of waves of AI,” Lievano said. “However, their eyes light up when we talk with them about new revenue opportunities,” Lievano said.
The research highlights that telcos possess critical assets few other industries can match: globally distributed data center capacity, secure and resilient networks, and deep, long-standing relationships with enterprise and government customers. But the barriers are equally significant — from proving the business case for AI infrastructure to navigating a shortage of data science and AI talent. Legacy technology debt continues to drag, with one executive lamenting that 145 years of accumulated systems make modern data integration “extraordinarily complex.”
A new Fierce Network Research report reveals how communication service providers are navigating the AI economy amid uncertainty about their role and strategy. (Google Gemini)
The bottom line is clear: to remain relevant in the AI-driven economy, telcos must modernize both infrastructure and business models — transforming from connectivity providers into intelligent digital enablers. However, we’ve heard that cry for telco transformation from dumb pipes to intelligent and autonomous network and IT providers, but it has yet to be realized. Will this time be any different?
References:
https://www.fierce-network.com/cloud/dumb-pipes-or-ai-powerhouses-telcos-face-identity-crisis
Full REPORT: “Risk, Reward and Revenue: Defining telcos’ role in the AI economy.”
Private 5G networks move to include automation, autonomous systems, edge computing & AI operations
Palo Alto Networks and Google Cloud expand partnership with advanced AI infrastructure and cloud security
Generative AI could put telecom jobs in jeopardy; compelling AI in telecom use cases
Generative AI in telecom; ChatGPT as a manager? ChatGPT vs Google Search
Allied Market Research: Global AI in telecom market forecast to reach $38.8 by 2031 with CAGR of 41.4% (from 2022 to 2031)
Markets and Markets: Global AI in Networks market worth $10.9 billion in 2024; projected to reach $46.8 billion by 2029
Ericsson integrates Agentic AI into its NetCloud platform for self healing and autonomous 5G private networks
Ericsson CEO’s strong statements on 5G SA, WRC 27, and AI in networks
New Linux Foundation white paper: How to integrate AI applications with telecom networks using standardized CAMARA APIs and the Model Context Protocol (MCP)
Vodafone Spain (Zegona), MasOrange and Telefonica in possible RANco joint venture
In an interview with Expansion published on January 26, 2026, Zegona [1.] CEO Eamonn O’Hare revealed that Vodafone Spain, MasOrange and Telefonica have been holding talks on the possibility of joining their mobile networks together since late last year. “We are talking with Orange and Telefónica to create a RANco,” he said.
Note 1. Zegona owns 100% of Vodafone Spain.
However, Zegona was unable to give the potential joint venture its full attention due to demands of its ongoing fiber projects. Telefonica and Vodafone created their Fiberpass joint venture (JV) in 2025 and agreed to sell a 40% stake to AXA in November. Meanwhile, Vodafone and MasOrange brought in GIC as an investor in their PremiumFiber JV last summer.
Eamonn O’Hare, president and CEO of Zegona
“The whole team was so involved in the fibercos that we didn’t have the time or energy to thoroughly develop the project,” O’Hare told the Expansion. Instead, his staff focused on tying up the fiber optic projects and then took a break over the Christmas period, he explained. “And now we’re back with more energy.”
Why a JV rather than a merger of telcos: “Mergers and acquisitions are not a priority in Spain and the regulatory risk is very high,” he said. Zegona has a greater motivation to make the RANco a reality. “Today there are three companies…that manage three national mobile networks with exactly the same fixed costs, but Orange and Telefónica have twice as many customers as us,” O’Hare explained. “Therefore, our national mobile network is inefficient. Just as our fixed infrastructure was inefficient and unprofitable, [and] that’s why we powered the fibercos.”
“It would be easier to broker a deal with MasOrange to share the network in certain areas, so the synergies would be in urban areas. But we don’t have anything with Telefónica, so there it would all be synergies.” Telefonica already has a mobile network sharing deal in place with Vodafone in sparsely populated areas, and was rumoured to be in talks with the telco on a broader RANco arrangement this time last year.
As a result, a partnership with Telefonica would bring greater synergies as there are no existing arrangements in place in the mobile space, but any deal would be a more difficult deal to hammer out and it would be trickier to bring in an investor, O’Hare added. Zegona has three priorities in Spain: to align its valuation with those of its competitors; to boost its cash flow to €1 billion; and to develop a RANco. “As long as we are in the middle of that transformation, we have no interest in mergers and acquisitions,” he said. And in addition, “the regulatory obstacle is…too big.”
“Historically, these small businesses have grown and then tried to sell themselves to MásMóvil. But MásMóvil no longer buys. Neither do we or Telefónica,” O’Hare said. “No one is buying. So they… will just be devoured by us and by Digi, as in the Pac-Man game.”
Would Huawei network equipment be used in the proposed Spanish RanCo? Vodafone is the mobile operator with the largest network provided by Huawei. Orange is reducing its share, and Telefónica only uses Huawei in part of its core network in Spain and not at all in its radio network. If the Brussels Cybersecurity Act mandates the replacement of this Chinese equipment, what will Vodafone Spain (Zegona) do?
“If Europe is more aggressive on the Huawei issue , I suppose we should accelerate efforts to reduce the amount of Huawei equipment in the network… should we accelerate RANco for this reason? Officially, the answer is no.”
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References:
https://www.expansion.com/empresas/tecnologia/2026/01/26/6973ab17468aebd1418b4590.html
SNS Telecom & IT: Private 5G Market Nears Mainstream With $5 Billion Surge
España hit with major telecom blackout after power outage April 28th
Orange Spain & Ericsson to build 5G Infrastructure for 3 High-Speed Rail Lines
Telefónica and Nokia partner to boost use of 5G SA network APIs
Telefónica launches 5G SA in >700 towns and cities in Spain
Telefónica – Nokia alliance for private mobile networks to accelerate digital transformation for enterprises in Latin America
Ericsson and O2 Telefónica demo Europe’s 1st Cloud RAN 5G mmWave FWA use case
Telecom and AI Status in the EU
STL completes successful Multi-Core Fiber (MCF) trial with Colt in London, UK
India based STL, a global provider of optical and digital connectivity solutions for AI-era networks, has completed multi-core fiber (MCF) field trials with Colt Technology Services on Colt’s London metro optical network. The trial is a meaningful proof point for space-division multiplexing (SDM) in carrier environments, demonstrating that MCF can lift per-fiber strand capacity while staying within existing civil and duct constraints and improving overall network energy and cost metrics.
The deployment used STL’s Multiverse™ four-core MCF, designed with the same 125 µm cladding diameter as conventional single-mode fibre (SMF) and a 250/200 µm coating, enabling seamless handling with existing cable designs and installation practices. The trial route connected two Colt Points of Presence (PoPs) on the London metro network over spans of approximately 9 km and 63 km, representing both short-haul metro and longer metro-regional use cases.
From a transmission standpoint, the network achieved an 800 Gbps line rate with service validation for 100GE and 400GE, aligning with current high-capacity router and data-centre interconnect interfaces. STL and Colt validated performance across a broad set of optical and system parameters, including chromatic dispersion (CD), polarization mode dispersion (PMD), inter-core crosstalk, throughput, fault behavior, OTDR signatures, insertion loss, and optical return loss (ORL), with results within expected design envelopes. This indicates that Multiverse™ MCF can be engineered and operated to comparable performance baselines as legacy SMF while delivering higher spatial capacity.
Architecturally, STL’s MCF platform integrates four independent cores within a standard SMF cladding profile, effectively multiplying per-fibre capacity without increasing cable diameter. For operators, this directly addresses constraints in congested metro ducts, legacy civil infrastructure, and brownfield routes where augmenting capacity by pulling additional cables is either cost-prohibitive or operationally disruptive. In these scenarios, MCF creates a higher bit-per-mm² and bit-per-duct investment profile, improving both capex efficiency (less civil work, fewer ducts) and opex metrics such as energy per transported bit.
STL positions itself as one of the early movers in taking MCF from controlled lab demonstrations into operational networks, including buried and ducted plant, backed by a full ecosystem spanning fibre, cable, and connectivity hardware through its Optotec portfolio. Coupled with STL’s broader focus on AI-ready optical infrastructure and 5G-ready digital network solutions, the Colt trial underlines a practical migration path for carriers looking to future-proof metro and data-centre interconnect footprints against emerging AI, cloud, and 5G traffic patterns without wholesale rebuilds of underlying passive infrastructure.
“As network demand accelerates, customers are looking for more bandwidth without sacrificing security, performance, or sustainability,” said Buddy Bayer, Chief Operating Officer, Colt Technology Services. “At Colt, we continue to push optical networking forward, and this pilot represents an important step in Europe and the USA. It reflects our focus on building scalable networks that deliver growth in capacity without increasing environmental impact.”
Dr Badri Gomatam, CTO, STL, said the trial highlights the value of joint innovation in advancing optical infrastructure. “Collaborations like this speed up adoption of next-generation connectivity technologies. STL’s Multiverse MCF portfolio is designed for the high-density, ultra-low latency, and resilient connectivity requirements of AI, hyperscale cloud, and future digital platforms globally,” he said. STL stated that the trial results strengthen confidence in MCF as a viable technology for the growing bandwidth requirements driven by AI workloads, cloud scale-out, and new digital services.
“As network demand accelerates, customers are looking for more bandwidth without sacrificing security, performance, or sustainability,” said Buddy Bayer, Chief Operating Officer, Colt Technology Services. “At Colt, we continue to push optical networking forward, and this pilot represents an important step in Europe and the USA. It reflects our focus on building scalable networks that deliver growth in capacity without increasing environmental impact.”
Dr Badri Gomatam, CTO, STL, said the trial highlights the value of joint innovation in advancing optical infrastructure. “Collaborations like this speed up adoption of next-generation connectivity technologies. STL’s Multiverse MCF portfolio is designed for the high-density, ultra-low latency, and resilient connectivity requirements of AI, hyperscale cloud, and future digital platforms globally,” he said. STL stated that the trial results strengthen confidence in MCF as a viable technology for the growing bandwidth requirements driven by AI workloads, cloud scale-out, and new digital services.
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About STL-– Sterlite Technologies Ltd:
STL is a global provider of advanced connectivity solutions, offering end-to-end products and services for building AI-ready networks across FTTx, rural broadband, enterprise, and data centres. With manufacturing operations in North America, Europe, and Asia, STL supplies connectivity solutions in more than 100 countries and works with telecom operators, cloud and data center companies, internet service providers, and large enterprises to build future-ready AI digital infrastructure.
On January 23, 2026, STL reported continued sequential improvement in Operational EBITDA margin for the fifth consecutive quarter, driven by a higher-margin product mix and increased contribution from the US market. With the US–India Bilateral Trade Agreement under advanced discussion, STL remains well-positioned to leverage emerging opportunities by offering reliable, high-quality solutions for building AI-ready digital infrastructure.
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References:
https://www.intechopen.com/chapters/78908
How will fiber and equipment vendors meet the increased demand for fiber optics in 2026 due to AI data center buildouts?
Big tech spending on AI data centers and
AT&T sets 1.6 Tbps long distance speed record on its white box based fiber optic network
Huawei Cloud Review and Global Sales Partner Policies for 2026
Huawei Cloud is the cloud computing platform of Huawei Technologies Co. Ltd., offering a comprehensive suite of cloud services and solutions for enterprises and individual consumers. It’s ranked as the second-largest cloud service provider in China by market share, consistently placing behind the market leader, Alibaba Cloud.
Huawei Cloud provides a full range of services including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS), supporting public, private, and hybrid cloud architectures. Cloud services include:
- Compute Services such as Elastic Cloud Servers (ECS), Bare Metal Servers (BMS), and container management via the Cloud Container Engine (CCE).
- Storage and Data Management Offerings include Object Storage Service (OBS), Elastic Volume Service (EVS), backup and disaster recovery solutions, and a range of database options like GaussDB and RDS for MySQL.
- Networking Services cover Virtual Private Cloud (VPC), Elastic IP (EIP), load balancing, and content delivery networks (CDN) to ensure fast and reliable connectivity.
- AI and Analytics This is a key focus area, featuring AI development platforms like ModelArts, pre-trained Pangu models, big data analytics services (MapReduce Service, Data Warehouse Service), and various AI-powered solutions for specific industries.
- Security and Compliance The platform offers robust security measures including firewalls, anti-DDoS services, data encryption, identity and access management (IAM), and comprehensive security operations centers.
- Developer and Management Tools A variety of tools for application development, operations management (O&M), migration, and governance.
Charles Yang, Huawei Senior Vice President, highlighted that the intelligent era presents immense opportunities and challenges for Huawei Cloud and its partners.
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- Global Visibility: Amplifying partner visibility through Huawei Cloud’s international media channels.
- Brand Enhancement: Assisting partners in improving their brand image using established global communication benchmarks.
- Enhanced Benefits: Upgrading partner benefits, including an increased Market Development Fund and comprehensive promotional support.
- Collaborative Marketing: Inviting partners to participate in Huawei Cloud’s own global marketing initiatives.
- Executive Level (CXO): Facilitating strategic exchanges on industry trends, digital transformation, and AI strategy to ensure vision alignment.
- Core Teams: Offering courses focused on business operations, industry analysis, and growth strategies.
- Sales and Technical Roles (BDs, SAs, CSMs): Providing hands-on training, including sales simulations and technical workshops, to enhance practical expertise.
References:
https://thetimes.com.au/news/press-releases?rkey=20260123AE69710&filter=24774
HUAWEI CLOUD launches partner programs in LatAm and Caribbean
Huawei’s Electric Vehicle Charging Technology & Top 10 Charging Trends
Huawei launches CloudMatrix 384 AI System to rival Nvidia’s most advanced AI system
Huawei to Double Output of Ascend AI chips in 2026; OpenAI orders HBM chips from SK Hynix & Samsung for Stargate UAE project
Omdia on resurgence of Huawei: #1 RAN vendor in 3 out of 5 regions; RAN market has bottomed
Blue Origin announces TeraWave – satellite internet rival for Starlink and Amazon Leo
The BBC reports that Jeff Bezos owned Blue Origin plans to create a new communications network called TeraWave, launching more than 5,400 satellites to offer global internet coverage. TeraWave will be focused on data centers, businesses and governments.
In a satellite internet market dominated by Elon Musk’s Starlink, Blue Origin would still have fewer satellites in orbit than Starlink. Yet TeraWave’s network at maximum speed would allow upload and download speeds of up to 6 terabits per second, much faster than rival commercial satellite offerings. The satellites are set to start launching by the end of 2027.
In April, Blue Origin launched an 11-minute space flight with an all-female crew, including Bezos’ now-wife Lauren Sánchez, singer Katie Perry and CBS presenter Gayle King. However, some commentators said it was “tone deaf” for celebrities to be taking part in such a fleeting and expensive trip at a time of economic struggle.
Blue Origin says TeraWave will be focused on data centers, businesses and governments. Blue Origin said its network, at its fastest, would allow upload and download speeds of as much as 6 terabits per second, much faster than rival commercial satellite services currently offer.
TeraWave is Optimized for Enterprise, Data Center, & Government Customers
- Starlink – part of Musk’s rocket firm SpaceX (which is 40% owned by Elon Musk) is by far the #1 satellite internet and phone service provider, primarily to individual customers.
- Blue Origin’s TeraWave satellite network will also compete with Amazon Leo, but they are targeting different market segments despite both being backed by Jeff Bezos. While it currently has around 180 satellites in orbit, having launched dozens more just last week, it plans to have more than 3,000 in orbit. Like Starlink, Amazon is also more focused on the general public than businesses and governments, positioning Leo as a way to offer high-speed internet access globally. It has not said when all of the Leo satellites will be in orbit.
| Feature | Blue Origin TeraWave | Amazon Leo (formerly Project Kuiper) |
|---|---|---|
| Target Market | Enterprises, data centers, governments, and other high-capacity users. | Consumers and communities in remote and underserved areas. |
| Service Goal | Provide extremely high-speed, symmetrical, and redundant backbone connectivity. | Deliver general high-speed broadband internet access (consumer speeds). |
| Projected Speeds | Up to 6 terabits per second (Tbps) via optical links in MEO. | Up to 1 gigabit per second (Gbps) for its highest-end user terminal. |
| Constellation Size | Plan for 5,408 satellites (LEO and MEO). | Plan for over 3,200 satellites (LEO only). |
In November, Blue Origin successfully landed a rocket booster on a floating platform for the first time. Only SpaceX had previously accomplished that feat.
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References:
https://www.bbc.com/news/articles/cn0yydwe89jo
AST SpaceMobile to deliver U.S. nationwide LEO satellite services in 2026
FCC grants Amazon’s Kuiper license for NGSO satellite constellation for internet services
Amazon to Spend Billions on 38 Space Launches for Project Kuiper
Starlink doubles subscriber base; expands to to 42 new countries, territories & markets
China ITU filing to put ~200K satellites in low earth orbit while FCC authorizes 7.5K additional Starlink LEO satellites
Amazon Leo (formerly Project Kuiper) unveils satellite broadband for enterprises; Competitive analysis with Starlink
Amazon launches first Project Kuiper satellites in direct competition with SpaceX/Starlink
NBN selects Amazon Project Kuiper over Starlink for LEO satellite internet service in Australia
Elon Musk: Starlink could become a global mobile carrier; 2 year timeframe for new smartphones
GEO satellite internet from HughesNet and Viasat can’t compete with LEO Starlink in speed or latency
Ericsson announces capability for 5G Advanced location based services in Q1-2026
Ericsson’s 5G Advanced location based services (LBS) offering is a comprehensive suite of innovations designed to redefine location-based services across commercial 5G Standalone (SA) networks. Set for release in Q1 2026, it makes Ericsson the leader in 5G positioning technology, offering a scalable and fully integrated solution on top of Ericsson’s dual-mode 5G Core network.
By embedding positioning as a core 5G SA network capability, Ericsson 5G Advanced location services enables Communications Service Providers (CSPs) to monetize precise location services and expand beyond traditional mobile offerings into verticals such as manufacturing, healthcare, public safety, automotive, drones, and more.
Key benefits:
- High Accuracy: Down to sub-meter for indoor and sub-10 cm for outdoor positioning, enabling precise tracking
- Scalability: Scalable, precise positioning for outdoor applications (automotive, agriculture, drones)
- Seamless Indoor/Outdoor Coverage: Unified 5G positioning technology for both environments.
- Developer & Device Friendliness: No need for device-side apps; improved battery life compared to satellite-based solutions
- Support for Large-Scale Use Cases: Enables massive geofencing, population density analysis, and tracking use cases.
Monica Zethzon, Head of Core Networks, Ericsson, says: “With the launch of 5G Advanced Location Services we are evolving the value of 5G Standalone networks. This innovation gives CSPs the precision and scalability to create differentiated services based on location capabilities.”
Caroline Gabriel, Partner at Analysys Mason, says: “Ericsson’s integrated approach to indoor and outdoor positioning sets a new benchmark in the industry. It addresses critical pain points for operators and enterprises, particularly in sectors where location accuracy is mission-critical.”
The global market for 5G positioning is in its early stages but poised for rapid growth, driven by demand for enhanced precision in diverse sectors. Ericsson’s solution responds to this demand with scalable, developer-friendly capabilities that improve device battery life compared to legacy systems.
This launch further strengthens Ericsson’s location solutions based on Real-Time Kinematics technology, with related devices from Ericsson planned for Q1 2026.
Photo Credit: Ericsson
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- Integrated Positioning: Positioning is built into the 5G Standalone (SA) architecture, moving beyond traditional GPS reliance.
- High Accuracy & Efficiency: New techniques improve accuracy (e.g., bandwidth aggregation, carrier-phase measurements) and reduce power consumption for devices.
- AI/ML Integration: Artificial Intelligence/Machine Learning is applied to enhance positioning accuracy, especially for challenging scenarios like beyond-visual-line-of-sight (BVLOS).
- Support for New Devices/Apps: Enables precise tracking for wearables, industrial sensors (RedCap), augmented reality (AR), drone control, and smart grids.
- Beyond-Line-of-Sight (BVLOS): Focus on reliable positioning for industrial and public safety applications where line-of-sight isn’t guaranteed.
- Reduced Power: Solutions target lower power usage, crucial for IoT devices.
- Release 18 (5G Advanced Start): Finalized mid-2024, introduced major LBS enhancements, including RedCap positioning, bandwidth aggregation, and carrier-phase support.
- Release 19 (Ongoing): Continues the evolution, extending LTM (L1/L2-triggered Mobility) and further exploring AI/ML for mobility and positioning.
- Release 20 & Beyond: Will build on these foundations, further evolving towards 6G capabilities.
References:
https://www.ericsson.com/en/press-releases/2026/1/5g-advanced-location-services
5G Advanced offers opportunities for new revenue streams; 3GPP specs for 5G FWA?
What is 5G Advanced and is it ready for deployment any time soon?
Hutchison Telecom is deploying 5G-Advanced in Hong Kong without 5G-A endpoints
China Mobile & ZTE use digital twin technology with 5G-Advanced on high-speed railway in China
Huawei pushes 5.5G (aka 5G Advanced) but there are no completed 3GPP specs or ITU-R standards!
ZTE and China Telecom unveil 5G-Advanced solution for B2B and B2C services
