Front of an ASUS GB300 NVL72 rack, showing its compute and switch trays

AI servers to full racks.

NVIDIA AI servers and rack-scale systems from leading OEMs, across current and upcoming generations, specified for your workload and the facility it will run in.

Choose the format.

We source OEM-built NVIDIA systems for GPU cloud operators and AI companies building or expanding their fleets. Bring a preferred platform, a full specification or just the workload you need to support.

Lenovo ThinkSystem SR680a V4 eight-GPU NVIDIA HGX B300 server

Eight-GPU servers

NVIDIA HGX platforms in a single chassis, for inference and fine-tuning, or as the building block of a larger cluster.

  • HGX B200, HGX B300 and HGX Rubin NVL8
  • Air- or liquid-cooled, depending on configuration
  • Scales out to clusters over the network fabric
A continuous frontal row of ASUS GB300 NVL72 racks in an illustrative AI infrastructure hall

Rack-scale systems

An entire rack built as one machine, for the largest training and inference workloads.

  • GB200 NVL72, GB300 NVL72 and Vera Rubin NVL72
  • 72 GPUs in one NVLink domain
  • Liquid-cooled; up to 142 kW per GB300 NVL72 rack

Rack power from NVIDIA’s GB300 NVL72 reference architecture. Configurations, cooling and supply terms are confirmed in each proposal.

Current and next generations.

Discuss systems across NVIDIA’s data-centre platforms, from Blackwell in service today to the Rubin generations that follow. You choose the platform for the workload; we are not tied to one generation.

Each quotation names the exact model and configuration, whether it is an NVIDIA-Certified System, and the support and supply terms.

NVIDIA

  1. BlackwellShipping
  2. Blackwell UltraShipping
  3. Vera RubinIn production
  4. Rubin UltraAnnounced
  5. Later generationsAs announced
Front of a Supermicro NVIDIA Vera Rubin NVL72 rack in an illustrative data-centre bay
Vera Rubin NVL72 rack (Supermicro)
Open NVIDIA Vera Rubin NVL72 compute tray with liquid-cooled modules
Vera Rubin NVL72 compute tray (NVIDIA)
Generation8-GPU serverRack-scale systemNVLink scale-up configurationGPU memory typeNVIDIA platform status
BlackwellHGX B200GB200 NVL72NVL72: 72 GPUs per rackHBM3eShipping
Blackwell UltraHGX B300GB300 NVL72NVL72: 72 GPUs per rackHBM3eShipping
Vera RubinHGX Rubin NVL8Vera Rubin NVL72NVL72: 72 GPUs per rackHBM4In production
Rubin CPX—Announced for context processingConfiguration to be confirmed—Announced; availability to be confirmed
Rubin UltraTo be announcedRubin Ultra NVL144 (Kyber rack)NVL144: one Kyber rack. NVL576: eight 72-GPU racks combinedHBM4E (announced)Announced
Later generationsAs announcedAs announced——Followed as NVIDIA announces them

From NVIDIA public product and roadmap material, checked November 2026. Roadmap details and timing are NVIDIA’s and may change.

Fit the system to the environment.

Networking, storage, rack space, power and cooling belong alongside the hardware specification. If you need somewhere to operate the systems, colocation can be part of the same discussion.

Explore colocation
  1. Dell PowerEdge XE9712 GB300 compute tray seen from above, with copper cold plates and liquid-cooling lines

    Compute

    GPU servers and rack-scale systems, chosen for the workload and the generation you want to run.

    • Platform and configuration
    • Quantity and delivery timing
  2. NVIDIA Quantum-X800 InfiniBand XDR switch, front view

    Network and storage

    The fabric that turns systems into a cluster, and the data paths that keep it fed.

    • Scale-up and scale-out fabric
    • Storage and connectivity
  3. Rooftop cooling plant with rows of dry coolers and maintenance walkways

    Power and cooling

    High-density racks move the constraint to power delivery and heat rejection, often liquid to the chip.

    • Power per rack and redundancy
    • Liquid cooling and heat rejection
  4. Data hall with rows of equipment cabinets and overhead power and liquid-cooling connections

    Facility and capacity

    Racks, a dedicated suite or a hall, in the right location, with room to grow.

    • Location and footprint
    • Term and expansion

What helps us quote.

A full specification or a first outline both work. Share what is decided and what is still open.

  • Preferred platform or system specification
  • Indicative quantity and configuration
  • Delivery country and target timing
  • Network, storage and facility requirements
  • Warranty and support requirements

Questions about AI systems.

Do we need a final specification?

You can start with a defined system or a broader infrastructure requirement. Share the information you have and the decisions still to be made.

Can we include networking and storage?

Yes. Include them in the brief; the quotation sets out what we propose to supply and how it connects to your wider infrastructure.

How are warranty and support handled?

Each quotation specifies warranty and support for the systems quoted. Tell us the coverage you need in your enquiry.

Which generations can we discuss?

Current Blackwell and Blackwell Ultra systems, Vera Rubin as it reaches the market, and later generations as NVIDIA announces them. Availability is confirmed per proposal.