NVIDIA is the much larger AI data-center business by reported revenue, while Marvell is a more specialized supplier of custom silicon, optical interconnects and networking. NVIDIA reported $193.7 billion in Data Center revenue for fiscal 2026, compared with Marvell’s $6,100.3 million for the fiscal year ended January 31, 2026. Those figures are not market-share measurements: the companies define and report their segments differently, and NVIDIA includes a broad accelerated-computing platform while Marvell emphasizes enabling components and customer-specific designs.
The more useful conclusion is not that one company simply replaces the other. NVIDIA supplies a vertically integrated platform built around accelerated computing, GPUs and networking. Marvell supplies custom application-specific silicon and connectivity that data-center operators can combine with larger platform ecosystems. Their March 31, 2026 NVLink Fusion announcement makes that relationship explicit: Marvell plans to contribute custom XPUs and compatible scale-up networking to NVIDIA’s ecosystem while the companies collaborate on additional infrastructure technologies.
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At a glance: what the reported numbers show
| Measure | Marvell | NVIDIA | How to read it |
|---|---|---|---|
| Fiscal period | Year ended January 31, 2026 | Year ended January 25, 2026 | The year-ends are different, so the periods are close but not identical. |
| Data Center revenue | $6,100.3 million | $193.7 billion | Company-reported segment revenue; definitions are not interchangeable. |
| Year-over-year Data Center growth | 46% | 68% | Each rate compares with that company’s prior fiscal year. |
| Share of total company revenue | 74% of $8,194.6 million | Data Center was the dominant contributor to $215.9 billion of total revenue | Marvell discloses the percentage directly; NVIDIA’s reported totals show the segment’s scale but are not the same disclosure format. |
| Primary role | Custom ASICs, interconnects, Ethernet, storage and networking components | Accelerated-computing platform including GPUs and networking | The companies participate at different layers of the infrastructure stack. |
| Latest cooperation relevant to AI infrastructure | Custom XPUs and NVLink Fusion-compatible scale-up networking planned | NVLink Fusion platform technologies and rack-scale components planned for integration | The March 31, 2026 announcement describes an announced collaboration, not completed deployments. |
For an investor, the first table answers the scale question but not the quality or durability question. NVIDIA’s segment is vastly larger in absolute dollars, yet Marvell’s concentration in data-center products gives AI demand an unusually direct effect on its company results. A smaller supplier can therefore have substantial exposure to the same buildout without being a competing GPU platform.
What Marvell sells into AI data centers
Marvell’s fiscal 2026 annual filing describes a portfolio of custom application-specific integrated circuits (ASICs), interconnects, Ethernet solutions, Fibre Channel adapters, processors and storage controllers. These products help customers move data, connect compute and storage, and tailor silicon to a particular system design. Marvell is consequently best understood as an infrastructure enabler rather than a single, standardized AI accelerator vendor.
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Custom silicon and customer-specific designs
A custom ASIC is designed for a defined workload or system requirement rather than sold as a general-purpose part for every buyer. In AI data centers, a large operator may want an accelerator, networking device or controller optimized for its own software, power envelope or deployment scale. Marvell’s custom-silicon business is aimed at that type of engagement. The filing also says the company was developing UALink and Ethernet for Scale-Up Networking switches for the emerging scale-out AI market.
Those development statements describe product direction, not a guarantee of commercial volume. They indicate where Marvell is investing: connecting large numbers of processors and accelerators and supporting the high-bandwidth communication that training and inference workloads require.
Optical interconnect and networking
Marvell’s 2026 proxy statement says optical interconnect represented roughly half of its data-center revenue. Optical links are used when electrical connections become difficult to extend at very high bandwidth or across longer distances inside a facility. The proxy also says custom silicon represented approximately 25% of data-center revenue. Both percentages are management characterizations published by Marvell; they should not be combined into a new, independently calculated revenue breakdown because the categories may overlap in how products are classified.
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Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstallMarvell’s broader list of Ethernet, Fibre Channel, interconnect and storage products gives it several ways to participate in an AI cluster even when it is not supplying the main compute accelerator. Its economic exposure can come from the data movement around an accelerator as well as from the accelerator-related custom logic itself.
What NVIDIA reports as its AI data-center business
NVIDIA’s fiscal 2026 results report $193.7 billion in Data Center revenue, up 68% year over year. Fourth-quarter Data Center revenue was $62.3 billion for the quarter ended January 25, 2026. NVIDIA also reported $215.9 billion in total fiscal 2026 revenue. The company’s annual review describes the Data Center platform as focused on accelerating compute-intensive workloads, including AI and data processing.
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A platform rather than a single chip
NVIDIA’s Data Center business includes GPUs and networking, but its strategic proposition is broader than either product category. Customers can buy accelerated-computing hardware, interconnects and associated platform technologies designed to work together. This integrated approach can simplify the design of an AI cluster and make the software, networking and compute layers more coherent than a collection of unrelated components.
The reported revenue does not establish how much came from any particular GPU generation, networking product or customer type. Nor does it prove that every dollar of Data Center revenue is AI revenue; NVIDIA explicitly describes the platform as serving AI and other data-processing workloads. The correct interpretation is that AI is a central driver of the segment, not that the segment is limited to one application.
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NVIDIA’s fiscal 2026 report says it introduced NVLink Fusion so hyperscalers and custom ASIC designers can integrate custom CPUs and XPUs with its platform. That matters because NVIDIA is not presenting its ecosystem as limited to NVIDIA-designed compute devices. It is also offering a way for customer-specific silicon to connect to NVIDIA’s interconnect and system architecture.
The announcement establishes a platform capability and an integration strategy. It does not establish the number of customers using those integrations, shipment volumes or revenue generated from them.
Why their revenue figures are not a market-share comparison
Comparing $6,100.3 million with $193.7 billion shows a dramatic difference in reported business scale, but it cannot tell you Marvell’s share of AI-chip sales or NVIDIA’s share of the entire data-center infrastructure market. Several distinctions matter:
- Different segment boundaries: Marvell’s Data Center segment includes custom silicon, interconnect, Ethernet, storage and related semiconductor solutions. NVIDIA’s Data Center platform spans accelerated computing, GPUs and networking and serves both AI and other data-processing workloads.
- Different fiscal year-ends: Marvell’s fiscal year ended January 31, 2026; NVIDIA’s ended January 25, 2026.
- Different business models: Marvell often supplies components or customer-specific designs that may be incorporated into another company’s system. NVIDIA reports a broader platform whose hardware and software are presented as an integrated offering.
- Different revenue recognition mixes: Product, system and platform sales can be recognized at different points in a supply chain. A component supplier’s revenue is not directly comparable with the final value of a complete accelerated-computing system.
Use the figures to assess relative scale and exposure, not to infer shipment share, installed-base share or technological superiority across every product category.
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Growth, concentration and business sensitivity
Marvell’s concentration cuts both ways
Data Center accounted for 74% of Marvell’s $8,194.6 million fiscal 2026 revenue. Marvell said Data Center sales increased 46% from fiscal 2025, driven by strong AI-related demand. Because such a large portion of company revenue comes from one end market, AI infrastructure spending can move Marvell’s consolidated results more directly than a similarly sized product line would at a diversified semiconductor company.
That concentration can amplify both upside and downside. Sustained deployments of custom accelerators, optical links and networking equipment could support rapid growth. A pause in hyperscaler capital expenditure, a customer redesign, inventory correction or delayed product qualification could have a noticeable effect on Marvell’s results because Data Center is such a large share of its base.
NVIDIA’s larger platform and cycle exposure
NVIDIA’s 68% Data Center growth rate and $62.3 billion fourth-quarter Data Center revenue show a business operating at a far greater scale. Its platform breadth can provide multiple ways to monetize a data-center buildout, from accelerated compute to networking and rack-scale systems. At the same time, the size of the segment means expectations, supply availability, product transitions and customer concentration can materially influence results even when absolute revenue remains high.
Neither growth rate should be projected mechanically. They are fiscal 2026 comparisons reported by the companies, not guidance for fiscal 2027 or a forecast of the overall AI market.
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How their products fit together in an AI cluster
| Infrastructure need | Marvell’s described role | NVIDIA’s described role |
|---|---|---|
| Compute acceleration | Custom ASICs and planned custom XPUs for specific customer requirements | Data-center GPUs and accelerated-computing platform technologies |
| Scale-up communication | Interconnects and planned Ethernet for Scale-Up Networking switches | NVLink interconnect and related platform technologies |
| Data-center networking | Ethernet solutions, Fibre Channel adapters and other networking silicon | ConnectX NICs, BlueField DPUs and Spectrum-X switches identified in the partnership announcement |
| Optical connectivity | Optical interconnect, described by Marvell as roughly half of Data Center revenue in its 2026 proxy | Participation through the broader platform and the announced silicon-photonics collaboration |
| System integration | Components and custom designs that can be incorporated into a customer’s architecture | Rack-scale AI-computing and platform integration |
This is why calling the companies interchangeable vendors creates confusion. A data-center operator could use NVIDIA’s accelerated-computing platform and still source particular custom silicon or connectivity from Marvell. Conversely, Marvell’s components can support systems whose principal compute platform comes from another supplier.
The March 31, 2026 NVLink Fusion partnership
Marvell and NVIDIA announced a strategic partnership on March 31, 2026, connecting Marvell’s custom silicon and networking capabilities with NVIDIA’s AI factory and AI-RAN ecosystem through NVLink Fusion.
What Marvell said it would provide
- Custom XPUs designed for customer-specific accelerated-computing requirements.
- NVLink Fusion-compatible scale-up networking.
- Collaboration on silicon photonics.
What NVIDIA said it would provide
- Vera CPU technology.
- ConnectX NICs and BlueField DPUs.
- NVLink interconnect.
- Spectrum-X switches.
- Rack-scale AI-computing technologies.
The announcement supports a view of competition and complementarity at the same time. Marvell can compete for parts of the custom-silicon and networking spend while using NVIDIA’s ecosystem as an integration path. NVIDIA can broaden the range of custom compute designs connected to its platform without giving up control of the surrounding interconnect and system technologies.
Keep the timing and status precise. This was an announced partnership and planned product contribution. The announcement alone does not establish customer deployments, shipment volume, production schedules or realized revenue. Marvell’s 2026 proxy similarly characterizes the relationship as connecting its custom silicon and networking capabilities to the NVIDIA AI ecosystem.
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If you want direct exposure to AI-platform spending
NVIDIA offers the more direct exposure to large-scale accelerated-computing demand because its reported Data Center segment is built around GPUs, networking and a unified platform. Its fiscal 2026 results provide the clearer measure of a company whose central growth engine is AI and data-center infrastructure.
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If you want a smaller supplier with concentrated infrastructure exposure
Marvell provides exposure to the enabling layer: custom ASICs, optical interconnect, Ethernet and related connectivity. The concentration of Data Center revenue means AI infrastructure trends can have an outsized effect on the company, but that also increases sensitivity to individual customer programs and spending cycles.
If you are assessing ecosystem optionality
The NVLink Fusion relationship is important because it gives Marvell a path into an NVIDIA-centered architecture while allowing NVIDIA to support customer-specific compute designs. An investor should treat that as strategic optionality rather than booked business until the companies report commercial deployments or revenue.
Questions to ask before drawing a conclusion
- Are you comparing platform revenue with component revenue as though they were the same product?
- Have you kept Marvell’s January 31 fiscal year-end separate from NVIDIA’s January 25 year-end?
- Are you treating the companies’ reported Data Center figures as market share? They are not.
- Are you separating reported fiscal 2026 results from development plans and partnership announcements?
- Does your thesis depend on AI demand continuing at the same growth rate? Neither company’s historical rate is guidance.
- Could a customer design change, qualification delay or inventory adjustment affect the supplier you are analyzing?
- Are you considering networking and optical interconnect as material parts of the AI infrastructure bill, rather than focusing only on compute chips?
Bottom-line comparison
NVIDIA is the clear leader in reported AI data-center business scale: its fiscal 2026 Data Center revenue was $193.7 billion, with a platform spanning accelerated computing, GPUs and networking. Marvell’s $6,100.3 million Data Center business is far smaller but highly focused, with custom ASICs, interconnects, optical technology, Ethernet and storage-related infrastructure representing the ways it participates in AI expansion.
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The companies therefore occupy overlapping but different positions. NVIDIA supplies a broad platform; Marvell supplies enabling and customer-specific technologies that can sit inside multiple architectures, including NVIDIA’s. The NVLink Fusion announcement reinforces that the relationship is not a simple winner-takes-all contest. For analysis, compare scale, growth, concentration, product layer and evidence of actual deployment separately instead of collapsing them into a single market-share judgment.
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