Digi Power X Deployed Nvidia Blackwell Chips
The company has integrated advanced AI hardware into its bare-metal server platform for enterprise clients.
Updated on Oct. 14, 2026 in Data Centers
Live Poll
Do you believe enterprise AI computing costs are becoming more affordable for your business?
Digi Power X has launched an AI computing platform powered by Nvidia Blackwell B200 and B300 GPUs. The infrastructure relies on Supermicro servers to support enterprise AI workloads.
Why it matters
By owning its power generation assets, Digi Power X can set rental rates based on actual costs rather than market premiums. This strategy allows the company to deploy new capacity in weeks instead of years without requiring massive capital expenditures.
The platform operates on a Tier III infrastructure standard using bare-metal servers that lack a virtualization layer. High-density, liquid-cooled racks are paired with rack-level environmental sensing to minimize physical floor space requirements.
The players
Digi Power X
This company is an enterprise AI infrastructure provider that maintains ownership of its own power generation and substation assets.
Nvidia
This technology corporation designs the Blackwell series of graphics processing units used for advanced artificial intelligence computing.
Supermicro
This hardware manufacturer produces the high-performance server systems utilized to house and operate GPU clusters.
The details
The platform utilizes a comprehensive software suite including SuperCloud Composer, SuperCloud Developer Experience, and SuperCloud Director. Integration of these tools enables the management of high-density AI clusters on private substations.
Timeline
The operational details of the AI platform were detailed on October 14, 2026.
The Tech Race
The integration of the Nvidia Blackwell GPU architecture signifies a shift toward dedicated, high-performance hardware for enterprise AI demands. This approach bypasses traditional virtualization, positioning the company against cloud providers reliant on shared server environments.
Enterprise customers gain access to faster AI model training times through the bare-metal architecture and liquid cooling improvements. Users may experience reduced compute costs resulting from the company's internal control over power generation and utility assets.
The takeaway
Companies prioritizing vertical integration of power assets can significantly reduce the time needed to scale complex AI infrastructure. Businesses looking to adopt similar architectures should weigh the benefits of bare-metal performance against the complexity of maintaining proprietary power grids.
Further reading
For more information on the evolving landscape of infrastructure, visit Data Centers.
Source note: This article includes information reported by Proactiveinvestors NA.
Live Poll
Do you believe enterprise AI computing costs are becoming more affordable for your business?
