Hardware

Dedicated Blackwell, down to the metal.

Eight GPUs to a node, ConnectX-8 SuperNICs on board, and InfiniBand fabric for clusters that act as one. No hypervisor, no shared lanes, no virtualization tax.

The lineup

Two nodes. Eight GPUs each.

Available now

B200 Node

SYS-A22GA-NBRT
GPUs
8× NVIDIA HGX B200
GPU memory
180 GB HBM3e per GPU
Interconnect
5th-gen NVLink (intra-node)
NICs
NVIDIA ConnectX-8 SuperNICs
Power draw
~14.5 kW per node
Form factor
Air-cooled rack node
Flagship

B300 Node

SYS-822GS-NB3RT
GPUs
8× NVIDIA B300 (Blackwell Ultra)
Interconnect
5th-gen NVLink (intra-node)
NICs
NVIDIA ConnectX-8 SuperNICs
Power draw
~19 kW peak / ~14.5 kW sustained
Density
4 nodes per 80 kW cabinet
Power feed
415 V 3-phase PDUs
Networking

One node or a hundred.

Single nodes run entirely on internal 5th-gen NVLink — no external fabric, no extra cost. When a job needs to span racks, nodes are stitched together with non-blocking InfiniBand (copper or optical) so a large cluster behaves like one machine.

InfiniBand is provisioned only for multi-node clusters — you don't pay for fabric a single node never uses.

  • Intra-node5th-gen NVLink, all 8 GPUs
  • Inter-nodeNon-blocking InfiniBand fabric
  • On-boardConnectX-8 SuperNICs included
  • TopologySized to your training job
Power & cooling

Built for sustained GPU draw.

GPU servers don't idle. Raw Metal deploys into power-dense colocation engineered to feed and cool them at full tilt.

80 kW
Per cabinet
415 V
3-phase PDUs
4
B300 nodes / cabinet
Air
Cooled, no retrofit
In every contract

What you get by default.

ConnectX-8 SuperNICs

Every node ships with NVIDIA ConnectX-8 SuperNICs on board — no add-on networking card to buy or wait for.

Full root access

Bare metal, end to end. Bring your own OS, drivers, CUDA, and orchestration. Nothing sits between your stack and the silicon.

Burn-in before handoff

Nodes are racked, cabled, and stress-tested in power-dense colocation. Fabric is validated before you ever log in.

Tell us what you're training.

We'll size the nodes, fabric, and cabinets around your workload.

Request capacity