Nvidia this week launched its latest Blackwell server GPU aimed at smaller enterprises using more traditional IT infrastructure, a development the company said will enable on-premises AI compute power at a lower cost.
Partnering with Cisco, Dell Technologies, HPE, Lenovo and Supermicro, enterprises will also have access to 2U Nvidia RTX Pro servers available in multiple configurations for workloads such as agentic AI, content creation, data analytics, graphics, scientific simulation and both industrial and physical AI.
For smaller, on-premises data centers, the CPU is still the workhorse handling IT infrastructure needs. But with demand for AI reaching a fever pitch, RTX Pro 6000 Blackwell Server Edition GPUs could be an attractive upgrade for smaller outfits, analysts said.
The RTX Pro 6000 GPUs could give smaller enterprise operations access to powerful accelerators that match their power and cooling capabilities. The lower-density GPUs combined with the more compact RTX Pro Server or other server configurations allow for air-cooling and fit into existing racks, providing plug-and-play upgrade possibilities.
“I see the RTX PRO 6000 and RTX Pro Server as Nvidia bringing Blackwell to the masses,” said Matt Kimball, vice president and principal analyst at Moor Insights & Strategy, in an email interview. He said RTX 6000 GPUs offer similar performance to the company’s top-of-line Blackwell Ultra, or B300, at a lower price tag.
“The RTX Pro Server brings all of these capabilities, right-sized for the non-large enterprise customer — think about the 5,000-employee, 1,000-server organization that wants to deploy agentic AI across the enterprise,” Kimball said.
Nvidia looks to increase GPU footprint
Justin Boitano, Nvidia’s vice president of enterprise AI, said Nvidia wanted to broaden its GPU and server portfolio based on demand from enterprise customers.
“A lot of enterprises have data centers that might have lower power densities or have air-cooled data centers,” he said in an email interview. “These RTX Pro Servers end up fitting brilliantly in that kind of traditional IT footprint. As we roll this out, we’re seeing a lot of interest across every vertical industry.”
Boitano said the GPU boost will enable enterprises to power virtual desktops and design applications, synthetic data generation, digital twins and more. “This infrastructure offers an accelerated computing platform that has the broadest capability,” he said. “As we really bring AI into this world of building agents and put them to work within our companies, we’re bringing the compute to the data.”
CPU-only servers are becoming stretched to their limits as enterprises explore use cases with more power needs. At the same time, more enterprises are moving back to on-premises or hybrid architectures to save on costs and increase security. CIOs were faced with the option of reinvesting in CPU-only architectures that are limited in AI workload capability or moving workloads to the cloud, according to Boitano.
“So it’s really not a huge risk to their business at this point, even to pause and reinvest that capital into AI infrastructure to get their company on this path of building and deploying AI,” he said.
Kimball said aiming at smaller enterprise customers was a good move for Nvidia’s overall market strategy. Main GPU rival AMD does not have a product aimed at smaller enterprises, he said. That left a big opening for Nvidia.
“I think Nvidia is smart in what it is doing with these platforms,” he said. “It is effectively seeding the commercial enterprise segment with an accelerated compute platform that can deliver value today — and tomorrow, when that organization is ready to adopt agentic AI enterprise-wide.”
Shane Snider, a veteran journalist with more than 20 years of experience, covers IT infrastructure at Informa TechTarget.
