NVIDIA makes most of its money selling data-center computing and networking products: in the quarter ended July 26, 2026, its Data Center platform generated $89.0 billion of the company’s $96.2 billion in revenue. The offer is broader than individual AI chips: it includes processors, networking, interconnects, integrated systems and software-enabled solutions. NVIDIA does not disclose a separate software revenue figure in the quarterly filing reviewed here.
Data Center is NVIDIA’s main revenue engine
For its second quarter of fiscal 2027, ended July 26, 2026, NVIDIA reported $96.2 billion in total revenue, up 106% year over year. Data Center revenue was $89.0 billion, up 117% year over year. That is about 92.5% of the quarter’s total revenue, making data-center products and related offerings the clear center of the business. These are quarterly results, not annual figures or a forecast. NVIDIA reported a 75.0% gross margin for the quarter and attributed the year-over-year improvement to a better mix from Blackwell Ultra.
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NVIDIA divides its Data Center platform into two customer markets. The latest recast figures in its Q2 FY2027 filing are:
| Data Center market | Q2 FY2027 revenue | What it covers |
|---|---|---|
| Hyperscale | $48.7 billion | Public cloud providers and the world’s largest consumer internet companies. |
| AI Clouds, Industrial, & Enterprise (ACIE) | $40.3 billion | AI cloud providers, industrial customers and enterprise customers. |
NVIDIA changed how it presents market-platform revenue beginning in Q1 FY2027 and later reclassified a company from ACIE to Hyperscale, recasting the affected comparative figures. The values above use the latest recast presentation in the Q2 filing, so older reports may show a different split.
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What customers pay NVIDIA for
AI chips and accelerated computing
GPUs and related processors provide the computing capacity used to train and run AI models, as well as other accelerated-computing workloads. NVIDIA sells these as components of a broader platform, rather than presenting its data-center business as GPU sales alone. The filing describes Data Center as including accelerated computing, networking, AI solutions and software.
Networking and integrated systems
Large AI installations need systems that connect processors and move data, not just individual chips. NVIDIA’s offer includes networking, interconnects and integrated data-center systems alongside compute. In Q2 FY2027, the company said Blackwell accounted for the majority of its system shipments and attributed Data Center growth to the ramp of Blackwell Ultra infrastructure. NVIDIA also said it was shipping both Blackwell and Rubin systems, so its product transition is ongoing.
This bundled approach helps explain why the financial results are reported for a broad Data Center platform rather than as a public tally of individual chip sales. NVIDIA’s filings do not provide a separate quarterly revenue figure for GPUs, networking, systems or software within that platform.
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Software and AI solutions are part of NVIDIA’s Compute & Networking operating segment description, and automotive software is included there too. This makes software relevant to how NVIDIA presents its platform, but the Q2 FY2027 filing does not report software as its own revenue line. The available disclosure therefore does not establish how much of quarterly revenue came from software, or support describing software subscriptions as a separately quantified major revenue stream.
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- NVIDIA Volta GV100 Architecture — 4,608 CUDA Cores, 640 1st-Gen Tensor Cores delivering 14 TFLOPS FP32 and 112 TFLOPS deep learning performance for AI training, inference, HPC, and scientific computing workloads
- 32GB HBM2 ECC Memory — 900 GB/s Bandwidth — High-bandwidth memory on a 4096-bit bus with ECC error correction provides the memory capacity and throughput required for the largest AI models, simulations, and datasets
- PCIe 3.0 x16 Interface — 250W TDP — Standard PCIe Gen3 connectivity with passive cooling designed for enterprise rack server deployment in HPE ProLiant, Dell PowerEdge, and Supermicro platforms with adequate chassis airflow
- NVLink — Scale to 96GB Unified Memory — Connect two V100 GPUs via NVLink at 300 GB/s bi-directional bandwidth to scale GPU memory from 32GB to 96GB for larger AI training and HPC workloads
- Multi-Precision Computing — Supports FP64 (7 TFLOPS), FP32 (14 TFLOPS), FP16 (112 TFLOPS) and INT8 precision modes for flexible deployment across training, inference, and scientific simulation workloads
AI-cloud partners and potential future revenue sharing
NVIDIA says select AI-cloud partners buy its data-center infrastructure and make cloud services available to third parties. As of July 26, 2026, NVIDIA disclosed $36 billion in commitments under these agreements, which typically run for six years. These commitments are not the same as revenue already recognized from product sales. If specified criteria are met, NVIDIA may receive a share of revenue generated by partners in the future; the cloud agreements can also be stopped by the AI clouds. Treat this as a conditional business model, not as current quarterly sales or guaranteed future income.
Other reported markets: Edge Computing, gaming and workstations
NVIDIA’s market-platform view has two categories: Data Center and Edge Computing. Edge Computing includes devices and applications that process data close to where it is generated, such as PCs, game consoles, workstations, AI-RAN base stations, robotics and automotive. It generated $7.2 billion in Q2 FY2027. Gaming and workstation graphics are part of the wider product picture, but the platform and segment reporting views classify activity differently.
In its operating-segment view, NVIDIA’s Graphics segment includes GeForce GPUs for gaming and PCs, plus Quadro and NVIDIA RTX GPUs for enterprise workstation graphics. These products are distinct from the Data Center market-platform figures above; do not add a segment figure to a platform figure as if they were separate pieces of one revenue total.
Why NVIDIA reports two different views of its business
Market platforms describe where products and solutions are used. Operating segments describe how NVIDIA groups businesses for financial reporting. The labels overlap, but they are not interchangeable.
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- Professional GPU with Blackwell Architecture
- Blackwell Architecture
- 24GB GDDR7 with PCIe 5.0 & Ray Tracing
- AI Workstation
| Reporting view | Categories | Examples described by NVIDIA |
|---|---|---|
| Market platforms | Data Center; Edge Computing | Data Center includes accelerated computing, networking, AI solutions and software. Edge Computing covers devices and applications such as PCs, robotics and automotive. |
| Operating segments | Compute & Networking; Graphics | Compute & Networking includes Data Center activity and automotive platforms and software. Graphics includes GeForce and Quadro/NVIDIA RTX GPUs. |
Because the two views classify activity by different criteria, their categories are not parallel revenue slices and should not be summed together. NVIDIA’s Q1 FY2027 release explained the market-platform reporting transition; the Q2 FY2027 filing supplies the later recast figures.
How sales reach customers—and where the risks sit
NVIDIA sells through channels serving cloud providers, AI labs and model developers, enterprises, public-sector customers, original equipment manufacturers, distributors and system integrators. The route to the end user can vary: a cloud provider may purchase infrastructure and sell computing access, while other customers may acquire systems directly or through a channel partner.
- Customer concentration: One direct customer represented 16% of NVIDIA’s total revenue in Q2 FY2027, primarily attributable to Compute & Networking. NVIDIA also says revenue is concentrated among a limited number of direct and indirect customers.
- Supply and demand volatility: NVIDIA reported supply constraints and cautioned that demand estimates can be inaccurate, which may make revenue or supply levels volatile.
- Partner-model uncertainty: Potential AI-cloud revenue sharing depends on specified conditions, and partner cloud agreements can be stopped by the AI clouds; it is not guaranteed recurring income.
The figures and reporting descriptions in this article come from NVIDIA’s Form 10-Q for the quarter ended July 26, 2026, its Q2 FY2027 earnings release dated August 26, 2026, and its Q1 FY2027 release on the reporting change.
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