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As AI infrastructure scales, I believe evaluating server network adapters solely by port speed or PCIe generation no longer tells the full story. Three factors are becoming increasingly important in shaping network architectures: performance, programmability, and power efficiency. Performance determines how efficiently data moves; programmability determines which infrastructure functions can execute outside the host CPU; and power efficiency influences system cost, cooling requirements, and deployment density.

According to Dell’Oro Group’s latest Ethernet Adapter & Smart NIC market forecast, the market is projected to grow to $53.6 B by 2030. As AI infrastructure investment accelerates, the more important question is not simply how fast the market will grow, but how evolving networking architectures will influence demand and competitive positioning across different adapter segments.

The NIC Paradigm: Balancing Performance vs. Programmability

As illustrated in the accompanying chart, general-purpose (GP) NICs, Data Processing Units (DPUs) and Infrastructure Processing Units (IPUs), AI-optimized NICs, and emerging scale-up transport occupy different positions along the performance-programmability spectrum. These are conceptual distinctions, not a linear progression: actual capabilities overlap and depend on implementation.

The deeper market question is not simply which adapter is fastest. It is where networking functions should reside—and which capabilities customers will pay to accelerate, offload, or integrate within their power and thermal budgets.

Different Workloads, Different Value Propositions.

 

General-purpose NICs

Connectivity as the baseline. General-purpose NICs serve enterprise, cloud, and data center workloads requiring reliable connectivity, compatibility, and cost efficiency. Their capabilities vary in bandwidth and hardware offloads. Where conventional connectivity meets workload requirements, additional processing may not justify its incremental cost.

For vendors, opportunities remain in cost-effective, easy-to-deploy 10/25G and 100G general-purpose Ethernet adapters. According to our Ethernet Adapter & Smart NIC research, Ethernet adapters operating at 100 Gbps and below are projected to account for 86% of port shipments in 2030 across the front-end networks of enterprises, non-AI cloud providers, and telecom operators.

 

DPUs/IPUs

Programmable infrastructure offload. Data Processing Units (DPUs) and Infrastructure Processing Units (IPUs) are programmable processors designed to offload networking, security, storage, and other infrastructure functions from host CPUs. Depending on the implementation, they combine general-purpose processor cores with networking engines and dedicated hardware accelerators to support virtual switching, security, storage, and infrastructure management. In our Ethernet Adapter & Smart NIC research, DPUs and IPUs are categorized within the Smart NIC segment, and Smart NICs are projected to account for 83% of NIC port shipments in hyperscalers’ front-end networks by 2030. The hardware data path engine or packet pipeline of a DPU/IPU (Smart NIC) can be implemented using either fixed-function ASICs or reconfigurable Field Programmable Gate Arrays (FPGAs).

As agentic AI increases infrastructure complexity through multi-step reasoning, tool orchestration, memory access, and policy enforcement, DPUs/IPUs may offer new opportunities to offload selected networking, security, and infrastructure tasks. The key market question is whether these demands will drive broader DPU/IPU adoption beyond established cloud deployments, which customer segments will lead incremental demand, and whether programmable offload will expand the Smart NIC market or intensify competition with AI-optimized NICs.

 

AI-optimized NICs

Performance at scale. Distributed AI training and accelerator-intensive workloads require high effective bandwidth, efficient transport, congestion management, and predictable latency. Specialized adapters may accelerate RDMA, supported transport protocols, and selected collective-communication functions.

Power efficiency is equally important. Indicative profiles range from approximately 15–30 W for some 400G fixed-function adapters to 40–75 W for some 800G-and-higher designs. Actual consumption varies by implementation. As port speeds rise, SerDes and PHY circuitry can add to the power and cooling burden. The relevant metric is therefore not bandwidth alone, but effective networking performance per watt. Across large clusters, adapter power contributes to rack-level heat removal requirements and can constrain system design.

These categories differ in emphasis, not absolute capability. AI NICs can incorporate sophisticated acceleration, while DPUs/IPUs can also support high-throughput networking.

 

Scale-Up Networking: An Emerging Frontier for AI Infrastructure

The next architectural shift may extend beyond faster conventional adapters. Scale-out networking connects servers through a fabric. Scale-up networking extends high-performance communication across accelerators, potentially spanning multiple racks. Depending on the design, this can introduce requirements for accelerator-aware communication, memory semantics, and coordinated endpoint and transport behavior.

Open Compute Project initiatives, including Ethernet for Scale-Up Networking (ESUN) and Scale-Up Ethernet Transport (SUE-T), illustrate this direction.

If these architectures mature and achieve deployment at volume, networking functions could move closer to accelerator silicon or into tightly integrated packages. This could change the role of conventional adapters and redistribute value among accelerator vendors, network silicon suppliers, and system designers.

While on-die scale-up networking is not yet covered in our Ethernet Adapter & Smart NIC research, we are closely watching how these emerging architectures evolve. Interoperability, software maturity, manufacturing, and customer qualification will determine which approaches gain commercial traction. Integration may reduce some data-movement overheads, but system-level power savings must be demonstrated rather than assumed.

 

Three Market Developments Shaping Ethernet Adapters and Smart NICs
  1. System-level performance

Higher port speeds alone do not guarantee better workload performance. Improvements in accelerator utilization, job completion time, and total system cost provide stronger evidence of differentiation.

  1. Economics of programmable offload

DPUs/IPUs can consume substantially more power than fixed-function adapters because they incorporate general-purpose processing and additional acceleration logic. That cost may be justified when offloading infrastructure functions reduces host CPU demand or improves isolation. The right comparison is net system-level power and performance, not adapter power in isolation.

  1. Scale-up deployment at volume

Standards progress and product announcements matter, but interoperability, customer qualification, and repeatable deployments are stronger indicators of commercial adoption. Product leaders should also assess whether emerging architectures improve power efficiency and thermal density at the system level.

 

The Strategic Implication

The AI networking market is unlikely to converge on a single adapter architecture. General-purpose NICs, DPUs/IPUs, and AI-optimized adapters address different requirements, while emerging on-die scale-up designs may change where connectivity and transport functions reside.

The deeper shift is not simply toward faster networking, but toward a redistribution of networking functions across the computing system. For vendors and infrastructure providers, success will depend on identifying which functions warrant dedicated hardware, which require programmability, and which may be integrated into the accelerator or fabric. The winning designs will balance performance, programmability, and power efficiency to deliver measurable system-level value.

As these architectures evolve, understanding the adoption and market positioning of Ethernet Adapters and Smart NICs will become increasingly important.

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One of the biggest themes at OCP 2026 was the remarkable level of optical innovation and announcements—activity historically more associated with OFC. In my observation, the number of sessions dedicated to optics nearly doubled compared with last year.

This shift goes beyond the conference agenda. As AI networks demand more bandwidth, denser connectivity and increasingly distributed architectures, optics and switching silicon are becoming more tightly intertwined. Six developments stood out.

1. Co-Packaged Optics Moves Closer to Commercial Deployment

Co-packaged optics (CPO) reached an important milestone as NVIDIA moved its Spectrum-X Ethernet Photonics switches into production, with early customer adoption and deployments beginning. Celestica reinforced that momentum with its DS6005, a liquid-cooled 102.4 Tbps Ethernet switch based on Broadcom’s Tomahawk 6–Davisson CPO platform. It offers 64 × 1.6 Tbps ports in a compact 1.5OU form factor, using co-packaged optical engines and field-replaceable external lasers.

Near-packaged optics (NPO) also deserves attention. In its rack-scale architecture announcement, Arista identified open CPO/NPO alongside XPO as next-generation optical approaches for increasing network-rack density, citing a path from 1.6 Pb/s with current OSFP-based designs to 6.5 Pb/s per rack. This is an architectural density outlook—not evidence that NPO is already shipping in volume.

 

2. Pluggable Optics Fight Back with Higher Bandwidth Density

Even as CPO gains momentum, pluggable optics are far from standing still. NVIDIA and Cisco introduced plans for Ultra-Dense Small Form Factor Pluggable (USFP), a proposed 400 Gb/s-per-lane design with a path to as much as 12.8 Tbps of aggregate module capacity.

The companies are targeting four times the bandwidth density and approximately 1.3 times the power efficiency of 200 Gb/s-per-lane pluggable designs. That could connect more endpoints without adding network tiers while retaining familiar deployment flexibility and field serviceability. The story is not simply CPO versus pluggables: adoption will reflect density, power, reach, reliability, operating model and economics.

The significance is that optical integration is progressing from component roadmaps to complete systems and rack-level design choices. Customer qualification, serviceability, production yields and meaningful shipment volumes remain the metrics to watch. Early commercialization should not be confused with broad adoption.

 

3. The 100T Switch Era Is Here—and the Transition to 1.6T Is Underway

The 102.4 Tbps generation is taking shape across multiple silicon and systems ecosystems. Broadcom’s Tomahawk 6 underpins Arista’s 7060XE7 portfolio, which supports dense 1.6 Tbps connectivity with air- and liquid-cooled options. Celestica’s Tomahawk 6-based DS6000 and DS6001 are available to order, while the DS6005 extends the family into CPO.

Cisco’s OCP 2026 update reported initial customer shipments of G300-powered 102.4T systems and introduced the 51.2T Silicon One G302, with 200G SerDes and 1.6T connectivity for top-of-rack applications; G302 shipments were planned for before year-end 2026. NVIDIA is also advancing Spectrum-6, including Meta’s announced adoption for next-generation AI infrastructure.

The direction is clear: 100T-class switching and 1.6T ports are becoming building blocks of AI fabrics. But market readiness differs across announcements, orders, customer sampling and shipments. The next question is when 1.6T moves into a sustained volume ramp.

 

4. Scale-Up Is No Longer Confined to the Rack

One of the most consequential architectural disclosures during OCP was Microsoft’s Maia 300 scale-up domain, described as connecting 12,288 accelerators across 128 racks. It combines electrical links within racks with optical inter-rack connectivity and custom transport for accelerator-to-accelerator communication. The implication is that scale-up can be defined by workload communication requirements, not simply physical rack boundaries.

Additional announcements reinforce the breadth of this shift. Arista’s Etherlink SU-144 proposes open, Ethernet-based scale-up for as many as 144 accelerators in a single-hop domain and up to 1,024 across racks. Celestica and AMD’s Helios collaboration focuses on scale-up switches using Ultra Accelerator Link over Ethernet (UALoE) for AMD’s rack-scale AI platform. These are distinct architectures and development stages, but both point to Ethernet moving deeper into accelerator interconnects.

Meta’s Tahan scale-up switch offers another concrete example: a 51.2T, Broadcom Tomahawk 5-based Ethernet switch in the MTIA 300 system, using a lossless RoCE approach under FBOSS. Meta says Tahan is shipping and has outlined a future 72-accelerator-per-rack platform on 102.4T silicon, with a roadmap toward Ethernet for Scale-Up Networking (ESUN).

OpenAI and Broadcom’s Jalapeño announcement adds the accelerator-design perspective. Jalapeño is an inference-focused processor, not itself an Ethernet scale-up switch; nevertheless, its broader system platform incorporates Broadcom networking technologies, underscoring how chip architecture and fabric design are increasingly co-optimized.

Together, these developments challenge a hard rack boundary between scale-up and scale-out. They also create new opportunities for switching silicon, optics and open Ethernet fabrics, while raising questions around latency, transport semantics, congestion control and operational complexity.

 

5. Competition in Scale-Up Switching Silicon Is Heating Up

The emerging scale-up opportunity is drawing new suppliers and architectures. Upscale AI introduced its 115.2 Tbps SkyFabriX switching silicon as part of its standards-oriented Token Fabric portfolio. Astera Labs also unveiled its Orion rack-scale PCIe switching architecture, aimed at connecting multiple accelerators within a pod.

These announcements reinforce two trends: suppliers beyond incumbent networking-chip vendors are targeting the market, and no single interconnect is likely to fit every workload. Ethernet, PCIe, NVLink, UALink, and emerging open standards will be evaluated against bandwidth, latency, memory semantics, flexibility and cost. Scale-up is becoming a meaningful new battleground for silicon share.

 

6. Hyperscaler Customization and Open Networking Keep Advancing

Meta’s OCP 2026 networking disclosure illustrates a multi-vendor approach. Its IcePack liquid-cooled rack houses 102.4T IceCube scale-out switches offered in two silicon variants: Broadcom Tomahawk6C and NVIDIA Spectrum-6. Both use Meta’s FBOSS software and OCP Switch Abstraction Interface (SAI). NVIDIA separately detailed its Spectrum-6-based N-IceCube collaboration. Cisco Silicon One belongs in the broader open-switching competitive landscape at Meta, although Meta’s disclosed IceCube variants did not identify Cisco silicon. Arista’s earlier R4/HyperPort announcement provides another example of the scale-across dimension, although that product announcement preceded OCP 2026.

Cisco’s OCP announcement highlighted Silicon One deployments across hyperscale networks, including P200 systems in Microsoft and Alibaba environments. NVIDIA and Google also announced Falcon Transport support for future ConnectX-10 SuperNICs and BlueField DPUs, extending interoperability between transport software and networking hardware.

These examples show hyperscalers combining merchant silicon with their own software, protocols and system designs. Openness, multi sourcing and interoperability are strategic choices—not just implementation details—as AI factories grow larger and more specialized.

 

Looking Ahead

If one message emerged from OCP 2026, it is that AI networking is no longer simply about faster switches. Optics, switching silicon and network architecture are co-evolving. CPO is entering early commercialization; NPO and other optical integration paths are gaining visibility; pluggables are pushing density higher; 100T systems and 1.6T connectivity are taking shape; and Ethernet scale-up is extending from the rack into larger accelerator domains.

Optics is no longer a supporting technology at the edge of the switching conversation. It is becoming an essential enabler of how the industry scales the next generation of AI infrastructure.

We provide deeper analysis of vendor positioning, customer wins, hyperscaler architectural choices and market adoption timelines, in our Data Center Switch—AI Back-end Networks reports. To access the reports, please contact us at dgsales@delloro.com.

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Liquid cooling and high-density power dominated the data center physical infrastructure agenda at a sold-out summit. In a week when credit markets fretted, the show floor shrugged.

 

Standing Room Only

The 2026 Open Compute Project (OCP) Global Summit closed on Thursday, October 15, as the largest edition yet. The event sold out, drawing roughly 15,000 attendees to the San Jose McEnery Convention Center, with about 3,000 more left on a waitlist. A year earlier, the count was less than 11,000. Many sessions were packed to capacity, starting with AMD CEO Lisa Su’s opening keynote on Monday. Shut out of packed rooms, attendees followed along on their phones from the hallways.

Lisa Su’s Keynote on October 12th, 2026

 

Relief is on the way. Next year, the summit moves to the Moscone Center in San Francisco, a substantially larger venue more in keeping with the stature OCP has gained in the AI economy. San Jose has been outgrown.

 

Pacing the Frontier, Racing the Buildout

On the floor, the mood matched the attendance. From concrete pourers to electrical engineers and thermal specialists, the people who build AI data centers have been working at breakneck speed for the past three years. Nothing on their order books suggests that is about to change.

Beyond the convention center, the backdrop was more uncertain. In September, Anthropic CEO Dario Amodei argued in “We Must Pace the Frontier” that AI developers should deliberately slow the advance of model capabilities, while stressing that pacing does not mean halting training. The frontier may be paced. The buildout is running at full throttle.

Credit markets fired a warning shot of their own. As the summit wrapped up, CoreWeave’s credit default swaps hit a record, pricing in more than 60% odds of default within five years. The topic came up in conversations, yet the crowd seemed unfazed. Sheer optimism prevailed, even if laced with a blasé disbelief at current growth rates.

 

Jensen’s Maths, Revised

On the IT side, optics stole the show. NVIDIA and Cisco introduced USFP, an optical module that fits four times the bandwidth into roughly the same space. Broadcom brought co-packaged optics, which sit right beside the switch chip to save power, and Wiwynn, Ayar Labs, and GUC showed the same approach on compute. Optical links are moving from the edge of the network toward the heart of the compute domain.

That migration changes what NVL576 means. At GTC 2025, NVIDIA unveiled Kyber as NVL576 by counting dies instead of GPUs: 144 GPUs with four dies each. Call it Jensen’s maths. NVIDIA has since dropped the die count, so Kyber got renamed NVL144. NVL576 has been repurposed. It now describes eight MGX racks of 72 Rubin Ultra GPUs each, joined into a single NVLink domain with copper inside each rack and optics between them. NVIDIA previewed the 576-GPU fabric again in San Jose—with NVL1152 expected to follow.

“Know Before You Flow — PG25 Mixing Thresholds for DLC” Session at OCP Global Summit 2026

 

For physical infrastructure, this is a subtle but consequential shift. Copper NVLink reaches only a few feet, which is why the scale-up domain has grown by packing more GPUs into a single cabinet. Optics loosen that constraint, blurring the line between scale-up and scale-out. If the domain can stretch across racks, the pressure to cram ever more silicon into one enclosure eases. Adding the migration of AI workloads from training to inference may cause the rack density trend to lose momentum.

But density is not going backward. NVIDIA’s MGX 1.2 specification supports racks up to 250 kW. Meanwhile, the OCP community sees a clear path to 1 MW racks—even if they arrive later and prove rarer than earlier roadmaps implied.

 

Plate Expectations

For the physical infrastructure community, the headline topics came as no surprise: liquid cooling and high-density power, the two pillars that make dense accelerated compute racks possible. Three shifts stood out on the floor. The cold plate took the spotlight from the coolant distribution unit (CDU). The 800 Vdc sidecar arrived in force. And solid-state transformers drew crowds well ahead of volume deployments.

At previous shows, the CDU took center stage. This year, it was all about the cold plate, the heart of direct-to-chip liquid cooling. This is not to suggest that CDUs were missing. CoolIT previewed its 3 MW CHx3000, integrated with Ecolab’s fluid monitoring suite, a sign that the acquisition is already bearing fruit. Cooler Master unveiled a 2.5 MW floor-mount unit, while Delta showed one of equal capacity running on 800 Vdc power. Rittal introduced an in-house CDU delivering more than a megawatt as part of its RiMatrix HPC architecture. Nidec, making its OCP debut, brought a 3.2 MW in-row prototype. Multi-megawatt is now table stakes.

The Project Deschutes design was also present, notably at the Envicool and Delta booths, the latter gearing up to mass-produce its Deschutes model in 1Q 2027. Yet it was eclipsed by the latest merchant designs. With the open specification at version 1.0 and a version 2.0 expected soon, some vendors may be holding fire. Others may see a design built around a single customer as not meriting the hefty investment of prime real estate on the show floor.

Deschutes CDU spotted at Envicool’s Booth

 

The real attention went to cold plates, where participation grew considerably. Established specialists such as Cooler Master and Auras continued to push the extension of direct liquid cooling beyond processors to memory, high-speed interfaces, and power delivery, while CoolIT unveiled its partnership with Stäubli on cold plates for pluggable optics. Jabil showcased the microchannel expertise it acquired with Mikros Technologies to handle more extreme heat fluxes. Start-up Frore Systems and IP specialist Adeia brought their own approaches, and xFusion presented diamond-copper composite cold plates. In the hallways and sessions, newcomers from adjacent industries, such as Conflux, were scouting their way into the data center.

As we detailed in our Data Center Liquid Cooling Advanced Research Report, every new silicon generation tests whether single-phase cold plates can keep up, turning a small component into a strategic asset. Large thermal management players have taken note. Earlier this year, Johnson Controls acquired Alloy Enterprises, whose stack forging process produces aluminum and copper cold plates, while Vertiv bought Strategic Thermal Labs, adding cold plate design and server-side validation. The show floor confirmed what the deal flow implied: value in liquid cooling is expanding beyond the CDU.

 

Phase Two: Two-Phase

If every new silicon generation puts single-phase to the test, two-phase direct-to-chip cooling is the contender waiting in the wings. The technology drew more interest in hallway conversations than in previous years, and both leading specialists came to make their case. ZutaCore demonstrated direct-to-die two-phase cooling on a running Blackwell GPU while MiTAC showed ZutaCore’s technology on its own servers. Accelsius answered with scale, expanding its Austin lab to multi-megawatt capacity for two-phase testing and teasing a 375 kW multi-rack unit. Beyond the specialists, Cooler Master previewed refrigerant-based cold plate loops still in development.

The OCP Foundation itself describes the transition to two-phase as looming, and a new OCP paper on thermal boundaries sets a threshold for single-phase cold plates that chip roadmaps may reach sooner rather than later. The interest likely reflects a growing sense of inevitability. Each year brings the two-phase era a little closer, but each year single-phase extends its runway a little further. Where one runway ends and the other takes off will constitute the battleground of the next few years.

 

Riding Sidecar

On the power side, the industry is coalescing around 800 Vdc, even if parts of the ecosystem, especially safety, protection, and insulation, still have ground to cover. OCP’s updated LVDC white paper now spans DC distribution up to 1,500 Vdc. Microsoft contributed new versions of its Mt Diablo power sidecar specification, which began life at ±400 Vdc. NVIDIA dedicated a session to protection and fault management, ABB and Eaton shared a keynote on the shift to DC distribution, and Vertiv explored how OCP could standardize the way solid-state circuit breakers behave and report faults.

Solid-state circuit breakers in the MGX Wall

 

Solid-state circuit breakers, designed to clear faults within microseconds, are getting closer to market, with SolarEdge and Infineon deepening their collaboration on a silicon carbide-based design. Electrical heavyweights ABB, Schneider Electric, Siemens, and Eaton also brought their own 800 Vdc protection and power hardware to NVIDIA’s MGX wall. The full chain still needs work. The industry has yet to determine the appropriate balance between solid-state and thermal-magnetic breakers, the design of DC PDUs, and how much battery and capacitance to install across the system—and where. Operating at these voltages also raises questions about arc-flash mitigation and controlling fault currents shaped by system inductance.

Even so, while the upstream 800 Vdc architecture remains an object of engineering ambition and speculation, the sidecar is here. Sitting beside the IT rack, it converts AC power to 800 Vdc, while taking the power shelves and battery backup out of the server rack. It was the star of the show—no, make that a constellation.

Traditional power shelf suppliers came out in full force. Delta displayed a 660 kW in-row power rack with 480 kW of integrated battery backup, Lite-On brought 800 Vdc racks and supercapacitor backup units, and AcBel, Advanced Energy, Murata, and Flex (soon to be spun off as Axiom Solutions) all staked out 800 V roadmaps. Facility power leaders Eaton and Vertiv were in the mix, too.

Then came the new entrants. Shenzhen-based Megmeet put 800 Vdc front and center, xFusion showed a sidecar prototype scaling from 300 kW to 1.2 MW, and white-label UPS manufacturer Voltronic Power joined the race. Perhaps most telling, auto parts giant Bosch is supplying its EV-derived 800 V power electronics for a Rittal sidecar demonstrator designed to scale to 2 MW. When the automotive supply chain shows up, a market has arrived.

Megmeet’s 800 Vdc Power Sidecar

 

Solid-State of Play

Solid-state transformers (SSTs), meanwhile, remain the darlings of the industry. Specialists DG Matrix and Heron Power exhibited at the show for the first time, both flush with capital after raising $60 million and $140 million respectively earlier this year. DG Matrix launched Interport 360 Flex, a skid-mounted system built on its SST cell that takes up to 34.5 kV AC and delivers native 800 Vdc. Solar power companies joined them on the MGX wall. SolarEdge displayed an SST cell while its full system undergoes validation, Sungrow showed components of its EnerNeo SST, and Delta demonstrated direct conversion from medium-voltage AC to 800 Vdc.

The hype is understandable. By folding the transformer, rectifier, and much of the switchgear into power electronics, the SST promises a leaner path from grid to rack. OCP’s draft SST design specification already targets units of up to 10 MW, with at least 98% efficiency from half to full load. Yet volumes remain modest, field reliability is unproven at scale, and protection and grounding practices are still being written. The real test will come as 800 Vdc moves upstream, from the sidecar to the facility.

 

Good Grid Citizens

Energy extended well beyond the rack. Google, Meta, Microsoft, and NVIDIA jointly published an OCP Grid Resilience Specification that targets restoring near-full load within two seconds of a grid disturbance. OCP launched a new Energy Project covering generation and storage, issued requirements for energy storage systems, and formed an alliance with EPRI and Current/OS on how data centers interact with the grid. On the floor, battery backup units, supercapacitor shelves, and fuel-cell microgrids sat alongside the racks they serve. The data center is learning to behave like a grid asset rather than just a grid load.

 

Quieter on the Newswire

Physical infrastructure giants were notably quieter on the newswire than a year ago. At OCP 2025, Vertiv, Eaton, Schneider Electric, ABB, and others rallied around NVIDIA’s 800 Vdc architecture with a wave of product previews and reference designs. This year, the majors spoke from the stage and the booth rather than through product launches. With so many vendors closely tied to NVIDIA, the bigger names may be saving their news for GTC Berlin, which opens on October 20. Industrial AI tops the agenda, befitting the heart of Europe’s manufacturing economy, and Siemens, Schneider Electric, ABB, and Vertiv are expected to arrive in force, announcements in hand.

 

Next Stop, Non-Stop to Moscone

Disruption is no stranger to the data center, and the ecosystem continues to evolve at speed. Across the products showcased in San Jose, OCP is pointing to what comes next. Energy is the topic at hand: from 800 Vdc distribution and solid-state conversion to storage and grid interaction. All in all, a great show. We look forward to seeing it in even greater scale at Moscone in 2027. In the meantime, you’re invited to connect with us at Dell’Oro Group to discuss these trends.

 

Off the Wire
Date Company Category Press Release
Sep 28 Murata Power Murata Showcases “Powering AI Scalability” at the 2026 OCP Global Summit
Sep 29 Infineon and Eaton Power Infineon and Eaton leverage silicon carbide technology to advance solid-state transformers for 800 VDC AI data center power architectures
Oct 5 Airsys and Shell Thermal Airsys and Shell Showcase Spray Liquid Cooling for Data Centers at OCP Global Summit
Oct 5 Navitas and Microchip Power The Data Center Is Moving to 800V: Microchip and Navitas Are Enabling the Transition
Oct 7 Nidec Thermal Nidec Debut Appearance at “OCP Global Summit 2026”
Oct 8 AcBel Power Acbel to Showcase High-Density Power Solutions for AI Data Centers at OCP Global Summit 2026
Oct 8 Delta Electronics Power & Thermal Delta to Showcase Energy-Saving Grid-to-Chip Infrastructure Solutions for Sustainable AI at OCP Global Summit 2026
Oct 8 Infineon Power Infineon introduces 27 kW three-phase PSU solution for next-generation AI server power architectures
Oct 12 Accelsius Thermal Accelsius Expands Austin Lab to Multi-Megawatt Capacity for Two-Phase Liquid Cooling Testing of Next-Generation AI Racks
Oct 12 CoolIT Systems Thermal CoolIT and Stäubli Advance Direct-to-Plug Liquid Cooling with Next-Generation Optics
Oct 12 Cooler Master Thermal Cooler Master Expands End-to-End Cooling Solutions for AI Infrastructure
Oct 12 Flex Power & Thermal Flex Expands Prefabricated Modular Data Center Portfolio to Accelerate AI Factory Deployment
Oct 12 Infineon Power Infineon introduces XDP8HD40S-1 high-voltage hot-swap controller
Oct 12 Navitas Power Navitas Collaborates with NVIDIA on 800 V-to-12 V Power Delivery Board for Next-Generation AI Infrastructure
Oct 12 Rittal Power & Thermal Rittal at the OCP Global Summit 2026: New Architecture for Extreme Power Densities
Oct 12 Texas Instruments Power TI unveils new ADC to enable nanosecond-level telemetry and minimize downtime in AI data centers
Oct 13 nVent Thermal nVent and AMD Collaborate on Cooling for AMD Helios Rackscale Solution
Oct 13 SolarEdge Power SolarEdge Showcases MVAC-to-800 VDC AI Factory Power Technology at OCP Global Summit
Oct 14 LITEON Power & Thermal LITEON Showcases NVIDIA 800 VDC Architecture and Thermal Management Portfolio at OCP Global Summit 2026
Oct 14 Nidec Thermal Nidec Unveils “NIR3.0” Prototype: A 3.2MW, 800VDC-Compatible In-Row CDU
Oct 14 xFusion Power & Thermal xFusion at OCP 2026: When Cooling, Power, and Interconnect Converge for the Agentic Era
Oct 15 Clivet (Midea) Thermal Clivet Showcases Next-Gen Magnetic-Bearing Centrifugal Compressor at OCP Global Summit
Oct 15 Delta Electronics Power & Thermal Delta Highlights Collaboration with NVIDIA in Advancing Energy-efficient 800 VDC Power and Cooling Solutions for AI Data Centers at OCP Global Summit 2026
Oct 15 LITEON Power LITEON Showcases at NVIDIA MGX Ecosystem at OCP, Highlighting 800 VDC Power Technologies to Advance Next-Generation AI Infrastructure

 

 

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Memory has become an increasingly important factor in the cost of data center infrastructure, particularly as data center capex is projected to soar past $3 trillion by 2030. Strong demand for conventional DRAM, which is used across all server types, and high-bandwidth memory (HBM), which is used in AI accelerators such as GPUs, has driven memory prices sharply higher. Supply constraints have further intensified pricing pressures, increasing the cost of both general-purpose and AI-optimized servers.

 

DRAM Inflation Could Add Hundreds of Billions to Server Spending

DRAM pricing has risen significantly over the past year. Dell’Oro Group currently projects server DRAM average selling prices (ASPs) to reach approximately $10/GB in 2026, before gradually moderating toward the $5/GB range by 2030.

The impact on server spending is substantial. As a sensitivity analysis, if DRAM ASPs were instead held at approximately $3.50/GB from 2026 through 2030, roughly in line with pricing prior to the recent increase, higher DRAM pricing could add nearly 10% to cumulative server spending through 2030.

The impact will be most pronounced in 2026 and 2027, when we expect DRAM pricing to remain near its peak. Pricing should begin to moderate more meaningfully from 2028 onward as additional supply enters the market and the industry responds to the higher cost of memory.

Our outlook for the overall DRAM market has consequently increased significantly. The increase is not driven by pricing alone. We have also raised our forecast for DRAM bit demand alongside higher server unit shipments, supported by emerging agentic AI and storage-related workloads that are increasing demand for general-purpose servers in addition to AI-optimized systems.

However, we do not believe today’s elevated DRAM pricing can persist indefinitely without affecting the pace of infrastructure investment. Memory suppliers are expanding production capacity, including new capacity from China, while server and processor vendors are developing more efficient approaches to memory utilization. Together, these developments should help alleviate supply constraints and gradually normalize DRAM pricing over the forecast period.

 

HBM Faces a Different Cost Challenge

HBM represents an even more important consideration for AI infrastructure. Demand will continue to rise as high-end accelerators incorporate increasing amounts of memory to support larger models and more memory-intensive inference and reasoning workloads.

We project the average high-end accelerator to contain more than 500 GB of HBM by 2030. That estimate could prove conservative. AMD’s recently launched MI455X, for example, already incorporates 432 GB of HBM, illustrating how rapidly memory capacity per accelerator is increasing.

Unlike conventional DRAM, however, HBM may not benefit from the same long-term cost-per-bit declines. Increasing stack heights, density, bandwidth, and packaging complexity could keep the cost per bit elevated even as the technology advances. As a result, simply scaling today’s HBM architecture to ever-larger capacities could significantly increase the cost of future AI systems.

Continued advances in HBM manufacturing and advanced packaging will therefore be critical. Technologies such as hybrid bonding, higher-density HBM generations, improved yields, and eventually lower HBM ASPs could help offset some of the cost associated with rapidly increasing capacity per accelerator.

At the same time, the industry may need to reconsider how much HBM actually needs to reside directly alongside each accelerator. NVIDIA’s Rubin Ultra, for example, could ultimately incorporate less HBM than the approximately 1 TB originally envisioned. Improvements in model efficiency and memory management could reduce HBM requirements, while emerging technologies such as high-bandwidth flash (HBF) could complement HBM as a lower-cost, higher-capacity memory tier.

 

Memory Efficiency Will Become Increasingly Important

The AI infrastructure industry has so far focused heavily on increasing compute performance, but memory economics could become an equally important constraint on future system design.

For conventional servers, elevated DRAM pricing could add hundreds of billions of dollars to infrastructure spending over the next several years. For accelerated servers, rapidly increasing HBM capacity and complexity could place additional pressure on already-high system costs.

Memory suppliers also face an increasingly complex balancing act in allocating production capacity across conventional DRAM, HBM, and NAND flash. With demand rising across servers, AI accelerators, and storage, suppliers will need to prioritize capacity and investment across these markets. The recent increase in DRAM and NAND pricing could make capacity expansion in these markets more attractive, complicating suppliers’ decisions on how aggressively to prioritize HBM production.

The industry response will therefore need to come from both sides: more memory supply and lower manufacturing costs, but also more efficient use of memory within servers and AI systems. Improvements in memory architecture, packaging, software, and additional memory tiers could become increasingly important in determining how economically the industry can continue scaling AI infrastructure through the end of the decade.

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Industrial giants are reshaping their portfolios at speed. Some are shedding non-core businesses to become focused pure-plays. Others are buying their way deeper into the data center. Both moves answer the same call: the AI buildout has become the industrial economy’s defining megatrend—and capital markets reward those who focus.

 

The End of the Everything Company

For most of the last century, scale and breadth were the point. General Electric was the template: jet engines, light bulbs, locomotives, medical scanners, home appliances, and a vast finance arm—all under one roof. Diversification was designed to smooth the cycle and compound the advantage.

Then investors stopped buying it. The complexity of these sprawling portfolios made them opaque to value and unwieldy to run. As a result, the market started applying a conglomerate discount, pricing the whole below the sum of its parts. A focused operator commands a higher multiple than the same business buried inside a diversified holding company. Breadth, in other words, was leaving money on the table.

GE eventually drew the obvious conclusion and broke itself into three: GE HealthCare, GE Vernova, and GE Aerospace. The logic now echoes across the industrial landscape. Honeywell is splitting into separate aerospace and automation companies while spinning off its advanced materials business into a new company, Solstice. United Technologies had beaten them to it back in 2020, separating into Carrier, Otis, and Raytheon.

 

Carrier’s Performing-While-Transforming Act

Carrier, born from that breakup, wasted little time before going further. Few companies have rebuilt themselves as aggressively. The throughline is simple: double down on intelligent climate and energy, exit everything else.

On the buy side, Carrier acquired Viessmann Climate Solutions, the German heating and heat-pump champion, for roughly €12 billion, with the deal closing in January 2024. It was a clear bet on the electrification of heat and on Carrier’s European core.

The sell side was busier. In a tightly choreographed portfolio transformation, Carrier shed the businesses that no longer fit. It sold Global Access Solutions, its security arm with the LenelS2, Supra, and Onity brands, to Honeywell for an enterprise value of $4.95 billion, around 17x EBITDA. Next came Industrial Fire and its Det-Tronics, Marioff, Autronica, and Fireye brands, sold to Sentinel Capital Partners for $1.425 billion. Soon it was Commercial Refrigeration’s turn, going to Haier for $775 million. And it capped the program by selling its Commercial and Residential Fire business to an affiliate of Lone Star Funds for $3 billion. An earlier exit, the sale of Chubb fire and security to APi Group, had already set the tone in 2021.

This is harder than a slide deck makes it look. Each carve-out means separating shared systems, renegotiating supplier contracts, staffing data rooms, and absorbing restructuring charges. All while hitting quarterly numbers and paying down the debt taken on for Viessmann. Carrier’s own framing, “performing while transforming,” was less a slogan than a description of the grind. CEO David Gitlin has noted that the divestitures were all signed within about a year of announcement, for a combined value of over $10 billion at a mid-teens EBITDA multiple in aggregate. The reward for the pain is a cleaner story and, the company is betting, a better multiple.

 

Johnson Controls Goes Pure-Play

A parallel story is playing out at Johnson Controls, a leader in data center thermal management. In August 2025, JCI completed the sale of its Residential and Light Commercial HVAC business to Bosch for $8.1 billion, including its residential joint venture with Hitachi. The move leaves JCI as a pure-play provider of building solutions, with around $5 billion in net proceeds and a $5 billion accelerated buyback.

The Bosch deal is the latest chapter in a long unwinding. JCI spun off its automotive seating business, Adient, back in 2016, then sold its lead-acid battery business, now Clarios, in 2019. Each step steered the company toward commercial buildings, and increasingly toward the data center. While paring the edges, JCI has reinforced the center, picking up hyperscale cooling specialist Silent-Aire and, more recently, direct-to-chip components maker Alloy Enterprises. The portfolio is getting narrower and deeper at the same time.

 

Trim Cooling to the Core

The pattern is spreading to HVAC players with one foot in other industries, which are now sharpening their focus on thermal and the data center.

Modine offers a clean example. In January 2026, it agreed to spin off its Performance Technologies business and combine it with Gentherm, in a Reverse Morris Trust. Performance Technologies, the company’s vehicular and power-generation thermal arm, carries about $1.1 billion in revenue. The transaction is valued at roughly $1.0 billion, around 6.8x post-synergy EBITDA, with Modine taking a $210 million cash distribution and its shareholders ending up with about 40% of the combined company. What Modine keeps is the prize: its Climate Solutions segment, now a pure-play built around data center cooling and commercial HVAC. Management expects that business to keep compounding, with data center demand growing well into the double digits. Modine has fed it through acquisitions, too, from Airedale to Scott Springfield and the TMGcore immersion assets.

Munters is running a similar play. The Swedish climate specialist has organized itself around three segments, AirTech, FoodTech, and a fast-growing Data Center Technologies unit that now drives close to 40% of sales. Sharpening that focus, Munters has moved to offload its FoodTech business while continuing to build on the data center side, where its 2024 acquisition of chiller maker Geoclima added liquid-cooling and heat-rejection capacity. The direction of travel is unmistakable: less food and agriculture, more AI factory.

These portfolio moves are part of a wider wave. Many of these companies had already been steadily increasing their data center exposure for years before any spin-off; the breakups and divestitures only accelerate a shift that was well under way.

Dell'Oro's analysis - Exposure of HVAC Companies Growing in Data Center
Source: Company Filings, Dell’Oro Analysis

 

Crossing Over to the Electrical Side

The same realignment is reshaping the power half of the stack, and the marquee move belongs to Flex.

In May 2026, Flex announced it would spin off its Cloud and Power Infrastructure segment into a new, independent public company, provisionally called SpinCo. The new entity will be a grid-to-chip play, integrating power distribution, thermal management, and full infrastructure systems for AI data centers and mission-critical applications. The growth profile is the headline: Flex is targeting 65% to 75% revenue growth for the new company in fiscal 2027, accelerating beyond 80% the year after. Current Flex CEO Revathi Advaithi will lead SpinCo, signaling where the company sees its future. The remaining Flex stays an advanced manufacturing partner, and the split is expected to close in early 2027.

What makes the Flex story instructive is how the segment was built. Flex assembled it through M&A, adding critical-power specialist Anord Mardix, switchgear maker Crown Technical Systems, and direct-to-chip cooling startup JetCool. Buy the pieces, build the platform, then spin it out to let the market value it on its own terms. It is the conglomerate discount thesis run in reverse.

Flex is not alone on the electrical side. GE’s split produced GE Vernova, a pure-play power and grid company. ABB agreed to hand its robotics division to SoftBank for $5.375 billion. nVent sold its thermal management business, the RAYCHEM and TRACER heat-tracing brands, to Brookfield for $1.7 billion, to concentrate on electrical connection and protection.

Dell'Oro analysis - Industrials Increasing Exposure to Data Center via Divestments
Source: Company Filings, Dell’Oro Analysis

 

No name, however, captures the realignment better than Eaton, which is also off-loading non-core assets. On June 2026, it agreed to separate its Mobility Group and combine it with Dana in a Reverse Morris Trust, valuing the vehicular business at about $5.1 billion and leaving Eaton shareholders with just over half of the combined company plus a $1.1 billion cash distribution. The spin-off sharpens its focus on electrical power.

But Eaton is not only shedding to refocus. It is also expanding inorganically. It added modular enclosure maker Fibrebond for $1.45 billion and solid-state transformer expertise through Resilient Power, building on earlier deals like Tripp Lite. The capstone is its $9.5 billion acquisition of Boyd Thermal, which vaults Eaton into liquid cooling at scale across CDUs, cold plates, and semiconductor thermal interface materials (TIMs), with the company guiding to roughly $1.5 billion in liquid-cooling revenue for 2026. With that cooling portfolio added to its electrical base, Eaton joins the ranks of vendors offering a full data center infrastructure stack.

 

The Full Stackers Get Fuller

While thermal and electrical specialists have reshaped their portfolios to raise their exposure to markets anchored in lasting high-growth fundamentals, the full stackers never had to. Already at the center of the digital infrastructure buildout, they have marched in a single direction: more power, more cooling, more of the stack.

Vertiv has been the most active. It strengthened white-space rack architectures by acquiring Great Lakes Data Racks & Cabinets for $200 million, around 11.5x EBITDA. It expanded its heat rejection and dry cooling offering with ThermoKey of Italy, adding EMEA manufacturing. And it reached up the thermal chain to the cold plate with Strategic Thermal Labs, adding server-side liquid-cooling design and validation. These sit alongside earlier moves into liquid cooling with CoolTera, into in-building power with E&I Engineering, and into commissioning and flushing services with PurgeRite. The strategy is end-to-end, grid-to-chip and across the lifecycle.

 

DellOro analysis - selected acquisitions and divestitures involving data center physical infrastructure vendors
Source: Company Filings, Dell’Oro Analysis

 

Schneider Electric has moved more selectively, favoring fewer but larger, high-conviction bets. In July 2025, it agreed to buy out Temasek’s remaining 35% stake in Schneider Electric India for €5.5 billion in cash, taking full ownership of one of its largest and fastest-growing markets. In cooling, it anchored its grid-to-chip ambitions with a 75% controlling stake in Motivair for $850 million. Motivair brings CDUs, cold plates, rear-door heat exchangers, and chillers, slotting directly into a portfolio that already spans power distribution and white space.

What unites them is a bet on breadth. Each is wagering that owning more of the stack will pay off, either by bundling additional products into the same deployment or by charging for the value of a coordinated, end-to-end design. The attach rate is never complete, and no vendor lands every power and thermal element in every project. But even a partial bundle, sold on the strength of a full-stack portfolio, can beat a point product standing alone.

 

New Entrants, Deep Pockets

If the incumbents are betting on breadth, another group is making a simpler bet: getting in at all. The most telling signal of this cycle is who is now arriving from outside the traditional infrastructure tent.

Ecolab, the water and hygiene giant, is the standout, and its move builds on a foundation laid years ago. Nalco Water, the treatment business it formed through the 2011 acquisition of Nalco for roughly $5.4 billion, already manages the cooling water that keeps data centers running. Moving from the facility loop to the fluid that cools the chip is the logical next step, and Ecolab took it by agreeing to acquire pure-play liquid-cooling specialist CoolIT Systems for $4.75 billion—a price 17 times what KKR and Mubadala paid only three years before. The premium is striking, but the opportunity behind it may be bigger still. As operators push warmer water through the technology cooling system (TCS) to chase efficiency, keeping that fluid clean and stable becomes a growing pain point, and few can answer it as completely as Ecolab, pairing CoolIT’s hardware with Nalco’s chemistry and the service to maintain both.

Others are crossing the same threshold. Samsung Electronics bought one of Europe’s largest HVAC makers, FläktGroup, for around €1.5 billion, planting a flag in data center precision cooling. Trane Technologies has built an end-to-end thermal stack with liquid cooling specialist LiquidStack and integrator Stellar Energy. Daikin Applied has reached into negative-pressure CDUs with Chilldyne and ultra-high-density cabinets with DDC Solutions. And on the electrical side, Legrand has run a near-continuous bolt-on campaign across busbars, racks, and power distribution, turning a steady stream of small deals into a serious data center franchise.

 

The New Megatrend

M&A in this sector is running hot, and there is little reason for it to cool down. We flagged as much in our 2026 predictions, where we expect still more deals to cross the $1 billion mark this year. As long as data center capex hovers around a trillion dollars, the business case for acquiring technical capability, manufacturing capacity, and customer relationships writes itself. No activist investor complains that a vendor is too exposed to the data center.

In an era of market exuberance, what makes this moment striking is the discipline. With capital abundant and investor appetite insatiable, an AI label on almost any acquisition would win expedited board approval. Yet the leading industrials are doing the opposite. Like a gardener pruning back the branches of a tree so it bears more succulent fruit, CEOs are reshaping the business for the AI age: offloading distraction, sharpening focus.

This is one of the AI buildout’s more unintended consequences. Industrial stocks have been among the market’s strongest performers in recent years. But the surging demand for electrical and mechanical equipment lifting their shares is only half the story. The bigger story is how AI is pushing these companies to remake themselves from within, unsettling the entire industrial ecosystem.

Industrial vendors have often coalesced around megatrends. For the past two decades, decarbonization and electrification set the agenda and shaped where capital flowed. Now, the AI buildout, and the next industrial revolution expected to ensue, is the dominant force—and the figures show how keen the industrials are to raise their exposure to it.

Are these industrial powerhouses making a mistake by tuning their portfolios to the AI buildout, or are they building a durable, long-term value-creation machine? Only time will tell. But unlike the software and internet companies that torched capital through the dot-com bubble, the industrials are taking a measured approach. And as they transform, they are emerging stronger, with leaner, more innovative portfolios better positioned to capture the opportunities that lie ahead.

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