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What do the latest data-center figures actually show?
The latest reviewed quarters are close in calendar time but are not the same reporting period: NVIDIA’s fiscal Q2 2027 ended July 26, 2026, and AMD’s Q2 2026 ended June 27, 2026. Both companies reported results in 2026. Their Data Center figures are company-defined segment or business-category revenue, not a like-for-like measure of accelerator sales.
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| Company and reported period | Data Center revenue | Year-over-year change | What the figure covers |
|---|---|---|---|
| NVIDIA, Q2 FY2027; quarter ended July 26, 2026 | $89.0 billion | Up 117% | Company-reported Data Center business; not GPU-only sales. NVIDIA Q2 FY2027 results |
| AMD, Q2 2026; quarter ended June 27, 2026 | $6.718 billion | Up 107% | Data Center segment includes EPYC processors and Instinct GPUs. AMD Q2 2026 results |
The revenue bases are far apart, but the reported growth rates are comparatively close. Neither observation by itself establishes GPU market share, the amount of revenue from AI accelerators, or the pace at which customers are adopting one vendor’s products. NVIDIA describes its platform as including compute, networking, data processing, and systems; AMD explicitly attributed Data Center demand to both EPYC processor and Instinct GPU demand.
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How should profitability be compared?
Start by checking whether each company discloses a metric at the same accounting scope. AMD reported $2.103 billion of Data Center segment operating income for Q2 2026 in its Q2 2026 Form 10-Q. The reviewed NVIDIA Q2 FY2027 release reports Data Center revenue, but not a directly comparable Data Center operating-income figure. It reports company-wide revenue of $96.221 billion and GAAP gross margin of 75.0%; neither is a Data Center segment margin.
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Segment operating income can help assess AMD’s reported segment performance, but it should not be treated as directly comparable to NVIDIA’s company-level gross margin. The measures describe different scopes, and segment cost allocation and definitions need not match. Avoid deriving a head-to-head segment margin from these figures.
For longer-period context, AMD’s fiscal 2025 Data Center segment reported $16.635 billion in revenue and $3.603 billion in segment operating income in its 2025 Form 10-K. NVIDIA reported $215.9 billion in total company revenue, up 65%, for fiscal 2026 in its Q4 and FY2026 results. These are different fiscal years and different revenue scopes, so they do not form a matched annual comparison.
What belongs in a platform comparison besides GPUs?
Data-center buyers and business analysts should compare the components needed to deploy and operate workloads, not just accelerator specifications. The companies’ 2026 releases identify different pieces of broader platforms:
| Area | NVIDIA disclosures | AMD disclosures |
|---|---|---|
| Accelerators and compute | Blackwell Ultra; Vera Rubin. NVIDIA said Vera Rubin was ramping into full production in its August 26, 2026 release. | Instinct MI400 family, including MI455X and MI430X; 6th Gen EPYC processors. |
| Systems and racks | NVIDIA described Blackwell Ultra infrastructure and named cloud partners running Vera Rubin racks. | AMD announced Helios rack-scale systems. |
| Networking and data processing | NVIDIA named Spectrum-6 networking and BlueField data-processing products. | AMD’s 2025 filing describes Pensando networking products. |
| Software | NVIDIA named CUDA-X in its Q2 FY2027 release. | AMD said ROCm.ai was released in its Q2 2026 materials; its 2025 filing describes ROCm framework and library support. |
These are company announcements and product descriptions, not independent evidence that every named product is broadly available or deployed at scale. AMD’s 2025 Form 10-K reports hyperscaler, OEM, and ODM deployments of MI350X during 2025, but the reviewed disclosures do not provide an equivalent adoption measure that supports a direct ecosystem ranking.
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Is AMD catching up to NVIDIA in AI chips?
“Catching up” depends on what is being measured. The latest reported growth rates show rapid expansion at both businesses, but the much larger NVIDIA revenue base, the different segment mixes, and the lack of GPU-only revenue figures prevent a simple conclusion about accelerator share or product parity.
For a useful assessment, separate the questions:
- Revenue scale: compare the reported Data Center totals while preserving the dates and category definitions.
- GPU-specific traction: look for disclosures that isolate accelerator revenue, deployments, or customer adoption; the figures above do not isolate GPU sales.
- Platform reach: consider CPUs, networking, systems, and software alongside accelerators.
- Workload portability: investigate which frameworks and libraries customers use and the engineering work needed to move applications. CUDA-X and ROCm/ROCm.ai are named in company disclosures, but the reviewed materials do not independently quantify adoption or switching costs.
NVIDIA CEO Jensen Huang characterized demand and monetization this way in the company’s August 26, 2026 earnings release: “AI has reached its inflection point. It’s doing useful work. Its tokens are productive and profitable. Now, compute is revenue.” This is Huang’s view, not an independently established measure of market-wide demand.
What execution risks could change the comparison?
Reported quarterly growth does not settle whether announced platforms will ship on schedule, reach customers at scale, or translate into durable economics. When assessing future performance, check product availability and ramp timing, customer deployment schedules, manufacturing and supply dependence, and export restrictions. A product announcement or management performance claim is not the same as verified broad availability or independently measured results.
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