Advanced Micro Devices (NASDAQ:AMD) shares gained 5% on Monday after Microsoft announced a major expansion of its strategic partnership with the chipmaker, positioning AMD’s latest AI hardware as a key component of Azure’s next-generation cloud infrastructure.
At the centre of the agreement is Microsoft’s large-scale adoption of the AMD Helios Rackscale Solution, which will support frontier AI model inference across Azure cloud services and enterprise workloads. The integrated platform combines AMD Instinct MI455X GPUs, sixth-generation EPYC “Venice” processors, Pensando networking technology and ROCm software into a unified rack-scale solution. Shipments are expected to begin during the second half of 2026.
Azure adds new AMD-powered AI virtual machines
As part of the expanded collaboration, Microsoft is introducing two new Azure virtual machine families based on AMD’s “Venice” architecture.
The HDv2 series is designed for agentic artificial intelligence and advanced data processing workloads, while the HXv2 series targets demanding semiconductor design applications that require high-performance computing resources.
The partnership also strengthens AMD’s role in Azure’s networking infrastructure. Microsoft plans to deploy AMD Pensando data processing units (DPUs) across its AI backend while integrating AMD silicon with Azure Boost to enhance networking performance throughout its cloud platform.
“AMD and Microsoft have spent years building high-performance infrastructure together, and today we’re extending that partnership across the full stack of AMD AI solutions on Azure,” said Dr. Lisa Su, Chair and CEO of AMD.
AMD strengthens position in hyperscale AI infrastructure
The broader agreement further establishes AMD as a major supplier of technology for hyperscale cloud providers, as demand for enterprise AI computing infrastructure continues to accelerate.
By expanding its footprint across computing, networking and AI software within Azure, AMD is strengthening its competitive position in the rapidly growing market for large-scale artificial intelligence deployments.
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