Positive<\/p>\n
-5.3%<\/p>\n
Zyphra launched an AMD GPU-powered AI cloud; shares fell 5.27%.<\/p>\n
Feb 24<\/p>\n
Strategic partnership<\/a><\/p>\n Positive<\/p>\n +8.8%<\/p>\n AMD and Meta announced GPU deployment plans; shares rose 8.77%.<\/p>\n Pattern Detected<\/p>\n Partnership-specific reactions were mixed, with one positive and one negative outcome; the tag-specific average move was 1.75%.<\/p>\n dpu<\/p>\n technical<\/p>\n “Azure deploys AMD Pensando\u2122 DPUs in AMD AI backend networking infrastructure”<\/p>\n Distributions per unit (DPU) is the amount of cash or income paid to each unit holder of a trust, real estate investment trust (REIT) or similar pooled investment for a given period. It tells investors how much cash income they received per unit, like getting a fixed slice of a pie for every share you own, and helps compare yield and judge whether the payout level is steady, growing or at risk.<\/p>\n rackscale platform<\/p>\n technical<\/p>\n “in an open, integrated rackscale platform built for large-scale AI training”<\/p>\n A rackscale platform is a data-center architecture that treats a whole rack of servers, storage, and networking as a single, pooled resource that can be configured and managed centrally. For investors, it matters because this approach can improve hardware utilization, simplify scaling and maintenance, and reduce operating costs for companies that run cloud, hosting, or large IT infrastructure\u2014like turning separate appliances into a modular toolbox you can rearrange on demand.<\/p>\n ai inference<\/p>\n technical<\/p>\n “to power frontier model AI inference for Microsoft, its AI customers”<\/p>\n AI inference is the step where a trained artificial intelligence model uses its learned patterns to analyze new data and produce an output \u2014 for example, predicting a stock trend, flagging a medical image, or generating text, much like using a recipe to cook a meal. It matters to investors because inference determines real-world performance, speed, and cost of AI features, affects user experience and scalability, and influences operating expenses, regulatory compliance, and competitive advantage.<\/p>\n AI-generated analysis. How Rhea-AI works<\/a>. Not financial advice.<\/p>\n
News Highlights<\/p>\n Microsoft to ramp AMD<\/a> Helios\u2122 at scale on Azure to power frontier model inference for Microsoft, its AI customers and Azure AI services. Azure will add two new VMs powered by 6th Gen AMD<\/a> EPYC\u2122 \u201cVenice\u201d processorsAzure deploys AMD<\/a> Pensando\u2122 DPUs in AMD AI backend networking infrastructure and select Azure services.The companies are integrating AMD silicon with Azure Boost to scale cloud networking performance across the fleet. <\/p>\n SANTA CLARA, Calif., July 20, 2026 (GLOBE NEWSWIRE) — AMD<\/a> (NASDAQ: AMD) today announced<\/a> an expanded strategic partnership spanning AMD GPUs, CPUs, networking and software on Microsoft Azure. At the center of this expansion, Microsoft will deploy the AMD Helios Rackscale Solution, to power frontier model AI inference for Microsoft, its AI customers and support Azure AI services. Azure will also add two new AMD EPYC CPU-powered VM series and broaden its deployment of Pensando DPUs to support Azure networking services. AMD will begin shipping Helios to customers, including Microsoft, in the second half of 2026.<\/p>\n AMD Helios combines AMD Instinct\u2122 MI455X GPUs, AMD EPYC\u2122 “Venice” CPUs, Pensando\u2122 networking and ROCm\u2122 software in an open, integrated rackscale platform built for large-scale AI training and inference. The Azure deployment will use Helios for inference workloads spanning frontier models, Azure AI services and customer applications.<\/p>\n \u201cAMD 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,\u201d said Dr. Lisa Su, Chair and CEO, AMD. \u201cMicrosoft’s new AMD deployments mark an important milestone as we deliver leadership compute solutions to Azure customers and scale the next generation of AI infrastructure together.\u201d<\/p>\n \u201cCustomers are looking for AI infrastructure that is\u00a0optimized\u00a0for a wide range of workloads, from training and inference to data preparation, search, and reinforcement learning,” said Satya Nadella, Chairman and CEO, Microsoft. “Through our collaboration with AMD, we are expanding the Azure infrastructure portfolio with AMD Helios to give customers the performance,\u00a0scale\u00a0and choice they need to build and run the next generation of AI applications.\u201d<\/p>\n The collaboration expands access to AMD AI infrastructure across Azure. Frontier model builders can now leverage AMD-powered infrastructure to train and serve large-scale AI models, while enterprise customers can deploy and scale production AI workloads through Azure Foundry Managed Compute.<\/p>\n Azure\u2019s new VM series, Azure HDv2 for agentic AI and data pipelines, and Azure HXv2 for semiconductor design, will be powered by 6th Gen AMD EPYC \u201cVenice\u201d processors. Together, the new VM series broaden Azure\u2019s AMD EPYC portfolio across AI, data and engineering workloads.<\/p>\n The collaboration also extends into the networking layer that connects and scales Azure infrastructure. Building on Microsoft\u2019s broad deployment of AMD Pensando DPUs, the companies are integrating Azure Boost with AMD technologies to improve networking performance, efficiency and connection processing at cloud scale.<\/p>\n As AI demand accelerates, AMD and Microsoft will continue to deliver open, high-performance infrastructure that gives customers flexibility, efficiency and scale to build what’s next.<\/p>\n Supporting Resources<\/p>\n About AMD<\/p>\n AMD (NASDAQ: AMD) drives innovation in high-performance and AI computing to solve the world\u2019s most important challenges. Today, AMD technology powers billions of experiences across cloud and AI infrastructure, embedded systems, AI PCs and gaming. With a broad portfolio of AI-optimized CPUs, GPUs, networking and software, AMD delivers full-stack AI solutions that provide the performance and scalability needed for a new era of intelligent computing. Learn more at www.amd.com.<\/p>\n Cautionary Statement<\/p>\n This press release\u00a0contains\u00a0forward-looking statements concerning Advanced Micro Devices, Inc. (AMD) such as\u00a0the features, functionality, performance, availability,\u00a0timing\u00a0and expected benefits of AMD products and expanded collaboration with Microsoft, which are made\u00a0pursuant to\u00a0the Safe Harbor provisions of the Private Securities Litigation Reform Act of 1995. Forward-looking statements are commonly\u00a0identified\u00a0by words such as “would,” “may,” “expects,” “believes,” “plans,” “intends,” “projects” and other terms with similar\u00a0meaning. Investors are cautioned that the forward-looking statements in this press release are based on current beliefs, assumptions and expectations, speak only as of the date of this press release and involve risks and uncertainties that could cause actual results to differ materially from current expectations. Such statements are subject to certain known and unknown risks and uncertainties, many of which are difficult to predict and are generally beyond AMD’s control, that could cause actual results and other future events to differ materially from those expressed in, or implied or projected by, the forward-looking information and statements. Material factors that could cause actual results to differ materially from current expectations include, without limitation, the following:\u00a0impact of government actions and regulations such as export regulations, import tariffs, trade protection measures, and licensing requirements;\u00a0competitive markets in which AMD\u2019s products are sold; the cyclical nature of the semiconductor\u00a0industry; market conditions of the\u00a0industries\u00a0in which AMD products are sold; AMD\u2019s ability to introduce products on a timely basis with expected features and performance levels; loss of a significant customer; economic and market\u00a0uncertainty; quarterly and seasonal sales patterns; AMD’s ability to adequately protect its technology or other intellectual property; unfavorable currency exchange rate fluctuations; ability of third party manufacturers to manufacture AMD’s products on a timely basis in sufficient quantities and using competitive technologies; availability of essential equipment, materials,\u00a0components (such as memory supply),\u00a0substrates or manufacturing processes; ability to achieve expected manufacturing yields for AMD\u2019s products; AMD’s ability to generate revenue from its semi-custom SoC products; potential security vulnerabilities; potential security incidents including IT outages, data loss, data breaches and cyberattacks; uncertainties involving the ordering and shipment of AMD\u2019s products; AMD\u2019s reliance on third-party intellectual property to design and introduce new products; AMD’s reliance on third-party companies for design, manufacture and supply of motherboards, software, memory and other computer platform components; AMD’s reliance on Microsoft and other software vendors’ support to design and develop software to run on AMD\u2019s products; AMD\u2019s reliance on third-party distributors and add-in-board partners; impact of modification or interruption of AMD\u2019s internal business processes and information systems; compatibility of AMD\u2019s products with some or all\u00a0industry-standard software and hardware; costs related to defective products; failure to maintain an efficient supply chain\u00a0as customer demand changes; AMD’s ability to rely on third party supply-chain logistics functions; AMD\u2019s ability to effectively control sales of its products on the gray market; impact of climate change on AMD\u2019s business; AMD\u2019s ability to realize its deferred tax assets; potential tax liabilities; current and future claims and litigation; impact of environmental laws, conflict minerals related provisions and other laws or regulations; evolving expectations from governments, investors, customers and other stakeholders regarding corporate responsibility matters; issues related to the responsible use of AI; restrictions imposed by agreements governing AMD\u2019s notes, the guarantees of Xilinx\u2019s notes and the revolving credit agreement; AMD\u2019s ability to satisfy financial obligations under guarantees, leases\u00a0and other commercial commitments; impact of acquisitions, joint ventures and\/or\u00a0investments on AMD\u2019s business and AMD\u2019s ability to integrate acquired businesses; impact of any impairment of the combined company\u2019s assets; political, legal and economic risks and natural disasters; future impairments of technology license purchases; AMD\u2019s ability to attract and retain key employees; and AMD\u2019s stock price volatility. Investors are urged to review in detail the risks and uncertainties in AMD\u2019s Securities and Exchange Commission filings, including but not limited to AMD\u2019s most recent reports on Forms 10-K and 10-Q.\u00a0\u00a0\u00a0<\/p>\n AMD, the AMD Arrow logo, AMD Instinct, AMD Pensando, AMD ROCm, EPYC and combinations thereof are trademarks of Advanced Micro Devices, Inc. Microsoft, Azure are trademarks or registered trademarks of their respective owners. Other names are for informational purposes only and may be trademarks of their respective owners.<\/p>\n Investor Contact
What did AMD (AMD) announce about its expanded AI partnership with Microsoft Azure on July 20, 2026?<\/p>\n
What is the AMD Helios Rackscale Solution Microsoft is deploying on Azure for AI workloads?<\/p>\n
When will AMD start shipping Helios systems to Microsoft and other customers?<\/p>\n
Which new Azure VM series will use 6th Gen AMD EPYC \u201cVenice\u201d processors?<\/p>\n
How will AMD Pensando DPUs be used in Microsoft Azure\u2019s AI networking backend?<\/p>\n
How are AMD technologies being integrated with Azure Boost to enhance cloud networking?<\/p>\n
What AI workloads will benefit from AMD-powered infrastructure on Microsoft Azure?<\/p>\n
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\n 07\/20\/2026 – 09:00 AM
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![\"\"](\"https:\/\/www.europesays.com\/ai\/wp-content\/uploads\/2026\/07\/Advanced-Micro-Devices-Inc-.png\")
Contacts:
\nAaron Grabein
\nAMD Communications
\n737-256-9518
\naaron.grabein@amd.com<\/p>\n
\nLiz Stine
\nAMD Investor Relations
\n720-652-3965
\nliz.stine@amd.com
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\n AMD announced an expanded strategic partnership with Microsoft Azure spanning GPUs, CPUs, networking and software. According to AMD, Microsoft will deploy the Helios Rackscale Solution to support frontier AI inference, Azure AI services and customer applications on Azure\u2019s cloud infrastructure.
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\n AMD Helios is an open, integrated rackscale platform for large-scale AI training and inference. According to AMD, it combines Instinct MI455X GPUs, EPYC \u201cVenice\u201d CPUs, Pensando networking and ROCm software, and will be used on Azure for frontier model inference workloads.
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\n AMD plans to begin shipping Helios systems to customers, including Microsoft, in the second half of 2026. According to AMD, these systems will support frontier model inference, Azure AI services and customer AI applications on Azure infrastructure.
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\n Azure\u2019s new HDv2 and HXv2 VM series will both use 6th Gen AMD EPYC \u201cVenice\u201d processors. According to AMD, HDv2 targets agentic AI and data pipelines, while HXv2 is designed for semiconductor design and broader engineering workloads on Azure.
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\n Microsoft is broadening deployment of AMD Pensando DPUs in its AI backend networking and select Azure services. According to AMD, these DPUs will support Azure networking services and integrate with Azure Boost to improve networking performance at cloud scale.
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\n AMD and Microsoft are integrating AMD silicon, including Pensando technologies, with Azure Boost to scale networking performance. According to AMD, this collaboration targets improved efficiency and connection processing across Azure\u2019s infrastructure as AI workloads and demand continue to accelerate.
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\n Frontier model builders and enterprise customers will both use AMD-powered infrastructure on Azure. According to AMD, frontier model builders can train and serve large-scale AI models, while enterprises can deploy and scale production AI workloads via Azure Foundry Managed Compute.
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