Member · NVIDIA Inception Program
Single-tenant NVIDIA clusters, delivered as a managed Kubernetes and Slurm platform, or straight bare metal with root. No shared silicon. No metered surprises. No procurement theater.
Member · NVIDIA Inception Program
GPU clusters engineered end to end for training and inference, not assembled from whatever the hyperscaler had left over.
Your workloads run on hardware allocated to you alone. No shared GPUs, no contention, no surprise throttling from a neighbor's training run. Deterministic performance, every run.
One number, agreed up front. No metered billing, no egress fees, no line-item archaeology at the end of the month.
Non-blocking Quantum-3 XDR InfiniBand at up to 800 Gb/s per GPU, plus NVLink inside the node. Gradients move at line rate.
Real dedicated capacity takes a quarter or more to allocate and commission. Anyone promising next week is reselling spare racks. We commit to a delivery date up front, in writing, and hit it.
A named solutions engineer who's seen your workload. Direct line, not a ticket queue and a four-hour SLA.
SOC 2 controls, private networking, encryption at rest and in transit. Your silicon is never shared with another org.
Take the keys however you want them: a running platform with managed Kubernetes and Slurm, a pre-tuned ML stack, and observability, or raw bare metal with root on every node.
$ kubectl get nodes
NAME STATUS GPU
gpu-001 Ready 8× B200
gpu-002 Ready 8× B200
$ srun --gpus=16 python train.py
nccl: all-reduce @ 780 Gb/s · 0 driver setupYou ship a workload; we run every layer beneath it. Kubernetes, Slurm, drivers, observability, all managed, patched, and tuned.
Root on every node, your stack on our fabric. We keep the hardware, network, and firmware healthy. The rest is yours.
Training a frontier model or serving millions of inference requests: the cluster gets built to match, not the other way around.
HIPAA-compliant, single-tenant GPU infrastructure for medical imaging, oncology research, and clinical decision support, backed by the NVIDIA Clara stack, reaching a network of 50,000+ clinics and medical offices.
Blackwell Ultra rack-scale systems and proven Hopper nodes, pre-validated to NVIDIA's NCP reference architecture, with Vera Rubin deployments already in flight.
FLAGSHIP · BLACKWELL ULTRARack-scale system for the largest training and inference runs. 72 Blackwell Ultra GPUs unified over NVLink 5 into a single coherent accelerator. We commission them up to 64 racks at a time.
You shouldn't have to fight a neighbor for bandwidth, decode a billing console, or hold your place in a capacity queue just to train a model.
Comet got us a dedicated GB300 cluster while we were still sitting on a hyperscaler waitlist. Multi-node training just worked, from the first run.
Single-tenant hardware means our runs are perfectly reproducible. No noisy neighbors, no surprise throttling. The fixed monthly cost made budgeting trivial.
Their team understands HIPAA at a depth no cloud provider matched. The BAA was signed before we finished scoping. That's why our clinical workloads moved over.
Tell us what you're building. We'll scope the cluster, quote a fixed monthly number, and commit to a commissioning date in writing. Dedicated capacity takes a quarter or more to stand up. The difference with us is that you'll know exactly when yours arrives.
