Companies › Semiconductors

AMD AMD

SemiconductorsMarket cap $250B13 connections

AMD broke Intel's monopoly on high-performance CPUs with its Ryzen and EPYC processors, which now power 30%+ of cloud servers. Its MI300X AI accelerator is the only credible alternative to NVIDIA's H100. Its Radeon GPUs compete with NVIDIA in gaming. AMD's chiplet design strategy - assembling processors from modular tiles - became the industry template for building complex chips affordably.

Explore AMD on the interactive map Relationship timeline Find a path to another company

Suppliers 3

Companies that sell to AMD

  • TSMCSemiconductors · $900BRyzen/EPYC chip manufacturing
  • SynopsysSemiconductors · $85BCPU verification tools
  • Cadence DesignSemiconductors · $80BChip design tools

Customers 3

Companies AMD sells to

  • AmazonConsumer & Retail · $2.0TEPYC CPUs for AWS EC2
  • MetaTechnology · $1.4TInstinct GPUs for Meta's AI data centres
  • OracleTechnology · $450BEPYC CPUs and Instinct GPUs for Oracle Cloud

Partners 3

Strategic partnerships, joint products and alliances

  • MicrosoftTechnology · $2.8TAMD chips in Xbox consoles
  • AlphabetTechnology · $2.1TCustom AMD chips for GCP
  • OpenAITechnology · $80BOpenAI to deploy AMD Instinct GPUs; OpenAI gains ~10% AMD stake

Competitors 4

Companies it competes with

  • NVIDIASemiconductors · $2.2TAI GPU rivalry
  • BroadcomSemiconductors · $800BAlternatives to NVIDIA AI chips
  • QualcommSemiconductors · $185BAI PC processors
  • IntelSemiconductors · $180Bx86 CPU rivalry

Key relationships in depth

AMD & Microsoft

AMD and Microsoft have an expanding partnership spanning Azure cloud AI infrastructure and Windows AI integration. Azure offers AMD Instinct MI300X GPU-powered VM instances (the ND MI300X v5 series) for AI training and inference, and Microsoft's Build 2025 conference featured AMD's ROCm software stack and Ryzen AI processors as a key pillar of Microsoft's on-device AI strategy for Windows 11. Microsoft also uses AMD EPYC server CPUs extensively across Azure's compute fleet.

Why it matters: Microsoft's Azure AI strategy requires GPU diversity to reduce dependence on NVIDIA and manage supply chain risk, and AMD's MI300X represents the most credible NVIDIA alternative at scale for large language model inference. On the client side, AMD's Ryzen AI NPU chips provide the hardware layer for Microsoft's Copilot+ PC features, giving Microsoft a second major silicon partner alongside Qualcomm for AI-capable Windows devices.

AMD & NVIDIA

AMD and NVIDIA are the two dominant competitors in the AI GPU and data center accelerator market, with NVIDIA holding approximately 86-92% AI chip market share and AMD as the primary challenger through its Instinct MI300X/MI350 GPUs and ROCm software ecosystem. NVIDIA's data center revenue reached $193.7B in fiscal year 2026 (ending January 2026), while AMD's data center segment grew 32% to $16.6B in 2025. Both companies compete for hyperscale AI training and inference contracts from AWS, Microsoft Azure, Google Cloud, and Meta, where NVIDIA's H100/H200/Blackwell architecture dominates but AMD is winning incremental workloads.

Why it matters: AMD's MI300X GPU with 192GB HBM3 memory offers a competitive memory capacity advantage for large language model inference that NVIDIA's H100 cannot match at equivalent price points. Microsoft Azure, Meta, and several cloud providers have deployed AMD Instinct GPUs for AI workloads to avoid full NVIDIA dependence and negotiate better pricing through dual-source competition. AMD's EPYC server CPU dominance (AMD holds the #1 position in x86 server CPU market share by units) gives AMD leverage in bundled CPU+GPU data center deals.

AMD & Alphabet

Google is a significant user of AMD EPYC processors in its data-center infrastructure as part of its multi-vendor CPU strategy alongside Intel Xeon and Google's own Arm-based Axion processors. Google Cloud also offers AMD EPYC-based virtual machine instances (N2D and C2D families) to GCP customers, competing with Intel's equivalent GCP VM families. Additionally, Google and AMD have explored collaborations in the AI accelerator space, though Google's TPU program remains its primary AI training platform.

Why it matters: Google diversifies its CPU supply across AMD, Intel, and its own Arm silicon to avoid single-vendor dependency and negotiate favorable pricing across its 3 million+ server fleet. AMD's EPYC processors offer Google a compelling performance-per-watt advantage over Intel Xeon in certain HPC and cloud workloads, allowing Google to allocate workloads optimally while maintaining competitive pricing on GCP VM instances.

AMD & Amazon

AMD and Amazon Web Services have a long-running CPU and accelerator partnership: AWS uses AMD EPYC processors in its C6a, M6a, R6a, and C7a general-purpose EC2 instance families, and AWS offers AMD Instinct GPU-powered instances for AI inference workloads. AWS's Graviton ARM chips compete with AMD EPYC for cloud compute share, but AMD remains a major CPU supplier for AWS's x86 fleet.

Why it matters: Amazon uses AMD EPYC to provide a competitive alternative to Intel Xeon in its EC2 fleet, delivering higher core counts and memory bandwidth at competitive prices that benefit AWS customers running compute-intensive workloads. AMD benefits from AWS's scale as the world's largest cloud provider, with even a modest share of AWS's server fleet representing millions of AMD processor units per year.

Other Semiconductors companies

Embed this on your site

Show AMD's network in an article or report - it updates as our data does.

Preview

Relationships are compiled by VexMap from company filings, announcements and reporting, and last reviewed September 2026. Spotted something wrong? Tell us. Not investment advice.