The Interconnection of Ai, GPU, Cloud

Written by Martin Wahlund

The Interconnection

The relationship forms a supply chain dependency loop:

  1. NVIDIA designs and manufactures GPUs (H100, A100, Blackwell series) that have become the industry standard for AI training and inference—over 62% of data center GPU usage goes to model training alone

  1. Cloud providers purchase NVIDIA chips at massive scale to power their infrastructure, then resell GPU compute capacity as a service to enterprises and AI developers

  1. AI companies/model builders either rent this capacity from clouds or buy hardware directly from NVIDIA to train and deploy models

This created NVIDIA's remarkable financial performance—revenues jumped 405% between 2023-2024, and the company became the first public company to reach USD 5 trillion market value in July 2025, with gross margins exceeding 70%.

The Major Players

Hardware Layer

PlayerPositionNotesNVIDIADominant leaderHolds majority market share; strategic investments in Nokia, Synopsys, GroqAMDStrong competitorGrowing institutional investment; alternative to NVIDIAHuaweiRegional dominant~28% market share in China due to export restrictions on NVIDIAIntel, Broadcom, MicronSupporting ecosystemMemory, networking components

Cloud Infrastructure (Hyperscalers)

  • Microsoft Azure — Major NVIDIA customer; integrates Copilot deeply with Azure AI services

  • Amazon AWS — Market leader in general cloud; offers P-series and G-series GPU instances

  • Google Cloud — Builds custom TPUs but still among NVIDIA's largest customers

  • Oracle Cloud — Signed $300B deal to provide compute to OpenAI; hosts NVIDIA DGX Cloud

  • Meta — Buys hundreds of thousands of GPUs directly for internal clusters (doesn't rent out)

  • SpaceX — Building AI data centers exclusively on NVIDIA hardware

Specialized GPU Cloud Providers

  • CoreWeave — NVIDIA holds equity stake; rents to Microsoft, OpenAI, Mistral

  • Nebius Group — GPU-native data centers for AI training

  • Nscale — Partnering with NVIDIA and OpenAI on "Stargate U.K." project

  • IREN — High-density compute clusters for enterprises

AI Model Developers

  • OpenAI — Major capacity consumer; partnered with Oracle, NVIDIA for UK infrastructure

  • Anthropic, Mistral — Rent capacity from specialized clouds

  • Google — Develops Gemini while also being infrastructure provider

  • Meta — Internal AI development; open-source models (Llama series)

Strategic Dynamics

  • Vertical Integration Risk: NVIDIA is actively investing across the stack (chip acquisitions like Groq for $20B in late 2025)

  • Sovereign AI Initiatives: Countries like UK partnering with NVIDIA to build national AI infrastructure

  • Geographic Dislocation: China developing domestic alternatives (Alibaba, Baidu, Huawei accelerators) due to export controls

  • Cloud Deployment: Approximately 58.6% of data center GPU market runs on cloud platforms versus on-premise

Martin Wahlund
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