Intel Accelerates Open Infrastructure for the Agentic AI Era
Key Highlights
- ➤Intel GPU D-series delivers 1.3 petaflops FP8 compute within 350 watts
- ➤GPU D-series supports up to 300 billion parameters per card
- ➤Select Xeon 6+ racks exceed 46,000 cores at 133.45 kW
- ➤Intel GPU D-series customer sampling is underway
- ➤Intel has made 116 Open Compute Project contributions since 2011
Expert Statements
Nicolas Dubé, Corporate vice president, Data Center Systems and Solutions Group, Intel
“Open models are expanding the options enterprises have for deploying AI”
Nicolas Dubé, Corporate vice president, Data Center Systems and Solutions Group, Intel
“To realize their full potential, organizations need infrastructure that can match different workloads with the right intelligence, right compute resources and right economics. That's what we mean by 'put every prompt in its place.'”
Anil Nanduri, Vice president, AI Products & GTM, Intel Data Center Group
“Inference is becoming the defining AI workload, and enterprises need infrastructure that delivers the right performance at the right cost”
Anil Nanduri, Vice president, AI Products & GTM, Intel Data Center Group
“With Intel GPU D-series, we're focused on making high-capacity inference practical to deploy and economical to scale.”
Kevork Kechichian, Executive vice president and general manager, Data Center Group, Intel
“Agentic AI is changing what customers need from their data centers. Success will depend not on any single component, but on open, heterogeneous infrastructure that brings together Xeon, purpose-built acceleration and interoperable software. Intel is helping customers build on their existing investments while creating a flexible foundation to scale emerging AI workloads efficiently.”
At the Open Compute Project (OCP) Global Summit today, Intel corporation shared new technical details on the Intel GPU D-series, formerly code-named Crescent Island, introduced new Intel Xeon-based rack designs and highlighted open software and ecosystem innovations.
As open models reshape the economics of agentic AI, demand is growing for more flexible, cost- and power-efficient infrastructure. Together, these advancements reinforce Intel’s approach to open, heterogeneous AI infrastructure, combining general-purpose compute, purpose-built acceleration, open software and standards-based systems to optimize performance and efficiency across AI workloads.
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