Vultr selected HPE and Nvidia GB300 NVL72 systems for AI inference deployments at HPE Discover 2026. The deal signals enterprise demand shifting from model training to production inference workloads.
Key facts
- Vultr deploys Nvidia GB300 NVL72 systems from HPE
- Includes Nvidia Spectrum-X Ethernet and HPE liquid cooling
- Financial terms, timelines, locations not disclosed
- Enterprise demand shifts from training to inference
Cloud infrastructure provider Vultr has selected Hewlett Packard Enterprise and Nvidia technology for a new wave of AI infrastructure deployments as enterprise demand switches from AI experimentation toward production workloads, according to Data Center Knowledge.
Under the agreement, Vultr plans to deploy Nvidia GB300 NVL72 systems supplied through the Nvidia AI Computing by HPE portfolio. The deployments will incorporate Nvidia Spectrum-X Ethernet networking and HPE liquid cooling technologies as part of new AI-focused data center environments. The companies did not disclose financial terms, deployment timelines, or the locations of planned facilities.
“Vultr represents a new generation of AI cloud providers, and the company’s selection of HPE validates the importance of AI data center architectures designed to support the next wave of global AI growth,” said Antonio Neri, president and CEO of HPE.
The deployment comes as AI infrastructure spending changes focus from model training to production inference workloads. Ron Westfall, vice president and practice lead for networking and infrastructure at HyperFrame Research, told Data Center Knowledge: “We have reached the inflection point where inference is transforming from a secondary operational phase into a primary, long-term driver of AI infrastructure investment.”
Production AI Takes Center Stage
Vultr CEO J.J. Kardwell said customer demand has shifted sharply over the past year from AI experimentation toward production deployments. Three years ago, most GPU demand came from startups and AI developers building and training new models, Kardwell said during a media briefing at HPE Discover. Today, a growing share comes from organizations running production AI services, including inference workloads tied to customer-facing applications and business operations.
“When you reach a point in the market where you're seeing operating margins for public companies be favorably impacted, we're now seeing changes to the way large public firms think about staffing levels because of the economic impact of these AI capabilities,” Kardwell said.
He said traditional enterprise procurement cycles are struggling to keep pace with the rapid evolution of AI infrastructure. Organizations accustomed to six- to eighteen-month planning cycles often find capacity unavailable by the time purchasing decisions are finalized, creating demand for cloud-based AI infrastructure.
The deal positions Vultr alongside CoreWeave and other GPU cloud providers racing to secure Nvidia's latest hardware. CoreWeave earlier this month beat AWS and Google to first Vera Rubin rack-scale validation, per our prior coverage. Vultr's choice of HPE as a partner—rather than direct Nvidia procurement—signals a bet on integrated, liquid-cooled rack solutions over commodity GPU clusters.
What to watch
Watch for Vultr's next capacity announcement—likely specifying deployment locations and timeline—as CoreWeave and others compete for Nvidia GB300 and Vera Rubin supply. Also monitor HPE's AI infrastructure revenue in its next quarterly earnings report.
Source: datacenterknowledge.com
