NVIDIA Corporation (NVDA): Who It Depends On
NVIDIA designs the GPUs and AI accelerators that power most of today's large-scale AI infrastructure, but it owns none of the factories that actually build its chips. Its business depends heavily on a small group of foundries, memory makers, and assembly partners to manufacture its hardware, and on a concentrated group of hyperscalers and system builders to buy it. Both dependencies are real concentration risks NVIDIA itself flags in its own SEC filings.
Supply-chain dependency
Companies NVDA relies on to design, manufacture, package, and assemble its hardware.
NVIDIA's disclosed foundry partner for producing its semiconductor wafers at leading-edge nodes, and the provider of CoWoS advanced packaging used to combine GPU dies with HBM memory. No other foundry currently matches TSMC's capacity or yields at this node, making it NVIDIA's single largest manufacturing concentration risk.
A leading supplier of the HBM (high-bandwidth memory) stacked onto NVIDIA's data-center GPUs, and historically NVIDIA's primary HBM3e source before Samsung and Micron ramped competing supply. Trades primarily on the Korea Exchange with no proper US-listed ticker.
A second major HBM and memory supplier to NVIDIA, ramping HBM4 production for NVIDIA's next-generation GPU platforms as demand for high-bandwidth memory continues to outstrip supply.
An alternate foundry and memory supplier named alongside TSMC and SK Hynix in NVIDIA's own filings, though it currently supplies a smaller share of NVIDIA's wafer and HBM needs than either. Trades primarily on the Korea Exchange with no proper US-listed ticker.
NVIDIA's named contract manufacturer for assembly, testing, and packaging of finished systems, including being the first supplier to ship complete GB200 rack-scale AI systems. Trades primarily on the Taiwan Stock Exchange with no proper US-listed ticker.
A key outsourced semiconductor assembly and test (OSAT) partner supporting the advanced packaging capacity NVIDIA needs to keep pace with GPU demand.
Supplies PCIe switch and retimer silicon and other networking components used across NVIDIA's AI server platforms to link GPUs together at scale.
Manufactures the high-speed connectors and cable assemblies - including NVLink interconnects - used to wire together NVIDIA's multi-GPU systems.
Supplies power distribution and liquid-cooling infrastructure for the dense AI data centers that NVIDIA's highest-power GPU systems require.
Provides power-management and voltage-regulation chips used on NVIDIA GPU boards and reference designs to deliver stable power to the GPU die.
Customer concentration
Companies that make up an outsized share of NVDA's revenue - who NVDA relies on to buy from it.
Azure's large-scale AI infrastructure buildout - supporting OpenAI, Copilot, and Microsoft's own AI services - makes it one of NVIDIA's largest cumulative GPU buyers.
Builds enormous GPU clusters in-house to train and run its Llama models and ad-ranking systems, buying NVIDIA GPUs in huge volume rather than relying solely on external cloud providers.
AWS deploys NVIDIA GPU instances at scale for its cloud AI customers, even as it develops its own competing Trainium and Inferentia chips.
Google Cloud sells NVIDIA GPU instances to enterprise AI customers alongside Google's own TPUs, and Google's internal AI teams are large GPU consumers in their own right.
Oracle Cloud Infrastructure has aggressively expanded AI infrastructure capacity - including large, multi-billion-dollar GPU cluster deals - built substantially on NVIDIA hardware.
A GPU-focused "neocloud" that rents out NVIDIA GPU capacity to AI labs and enterprises, making it one of NVIDIA's largest customers by concentrated GPU purchase volume.
A top OEM partner that integrates and resells NVIDIA GPUs inside its enterprise AI server lineup.
A high-volume systems integrator that builds and ships GPU-dense AI servers, making it one of NVIDIA's largest direct hardware customers by unit volume.
Sells NVIDIA-powered AI servers through its enterprise hardware lines to corporate and government AI buyers.
Has historically purchased large volumes of NVIDIA GPUs for AI model training, even as it invests in its own custom silicon.
The percentages shown are editorial estimates based on public research (company filings, earnings commentary, and industry reporting) meant to illustrate relative reliance, not precise or audited figures - NVIDIA does not publish an exact "reliance percentage" for any single supplier or customer. Companies without a proper, reliably tradable ticker on this site are shown without stock/earnings links. This is not financial advice.