What NVIDIA does
NVIDIA Corporation is a public semiconductor and AI computing platform company that designs GPU and CPU architectures, networking and data-processing units, and full-stack systems and software used to build and operate accelerated computing environments. In recent years, NVIDIA’s platform strategy has centered on AI training and inference at data-center scale (including rack- and supercomputer-scale systems), plus a growing set of “AI computer” offerings aimed at enterprise and developer workflows. Core to this model is a vertically integrated stack that combines compute hardware (e.g., GPU/CPU superchips), high-speed networking (e.g., InfiniBand/Ethernet switching), and software platforms and microservices available through NVIDIA’s GPU cloud and enterprise software catalogs.
NVIDIA’s platform approach is visible in its product line spanning: - Compute and systems: Blackwell-based data center platforms (e.g., GB200 “Grace Blackwell” superchips and rack/system configurations) and other data-center systems; and newer “developer-sized” system offerings such as NVIDIA DGX Spark. - Networking and data processing: NVIDIA Spectrum-family networking and BlueField data-processing units are positioned as integral to end-to-end performance and productivity in AI infrastructure. - Software: NVIDIA AI Enterprise provides a software reference architecture and enterprise-supported components; NVIDIA NIM microservices and related developer tooling are distributed through NVIDIA’s NGC ecosystem.
Business model and target users: NVIDIA sells high-performance hardware and system configurations to hyperscalers, enterprises, government/research organizations, and channel partners, and also monetizes software and platform access via enterprise licensing and subscription-like mechanisms tied to software stacks and catalogs. NVIDIA’s customer-facing platform messaging emphasizes lowering cost and energy per token, improving deployment speed across cloud/on-prem environments, and integrating across the stack so that developers and infrastructure teams can move from model/workload selection to production inference/training pipelines more quickly.
Strategic position (as of the latest publicly available materials): NVIDIA is actively expanding both its infrastructure footprint (e.g., partnerships for large GPU deployments) and its platform surface area by launching new compute/network/storage building blocks for agentic AI and “AI factories,” while also extending into software/platform layers such as developer ecosystems and model distribution. In September 2026, NVIDIA announced it agreed to acquire Hugging Face, signaling a further push into developer and open-model distribution channels that complement NVIDIA’s hardware and software stack.