Your own GPU cluster.
Fully managed.
Dedicated bare-metal GPU infrastructure with the scheduler, the orchestration, and the 24/7 operations included. You get root on real hardware; we keep it healthy, fast, and full.
Single-tenant by default, no hypervisor, no shared GPUs, no noisy neighbours. Deployed in Tier III facilities across the US, Canada, Mexico, Europe, and Asia.
Dedicated nodes and a dedicated fabric. Your throughput is never someone else's job queue.
Slurm or Kubernetes stood up, tuned, and operated, so your researchers ship instead of babysitting infrastructure.
Design, build, burn-in, acceptance test, handover. A real deployment window in writing.
The cluster, and everything that keeps it running.
Take the hardware alone, or take the whole stack. Most teams take the whole stack, because the scheduler and the 3 a.m. link flap are the parts that actually cost engineering time.
Bare Metal GPU
Dedicated, single-tenant GPU nodes with root access and no virtualization tax. Non-blocking InfiniBand or RoCEv2, NVMe local scratch, and shared high-throughput storage.
- Tenancy
- Single-tenant, dedicated
- Platforms
- H100 / H200 / B200 / B300 / GB300 NVL72 / MI300X
- Fabric
- InfiniBand or RoCEv2, non-blocking
Managed Slurm
A research-grade scheduler stood up, tuned, and operated for you: partitions, QoS, fair-share accounting, container support, and job telemetry.
- Scheduler
- Slurm, tuned per workload
- Containers
- Pyxis / Enroot / Apptainer
- Included
- Accounting, telemetry, upgrades
Managed Kubernetes
Production Kubernetes with the NVIDIA GPU operator, autoscaling node pools, ingress, and full observability. Cluster lifecycle and upgrades are ours to carry.
- Distribution
- Upstream-conformant K8s
- GPU
- GPU operator, MIG or time-slicing
- Included
- Observability, ingress, lifecycle
Operations & Maintenance
24/7 NOC coverage, hardware sparing and RMA, firmware and driver lifecycle, fabric health, and thermal monitoring, on our fleet or on hardware you already own.
- Coverage
- 24/7 NOC, SLA-backed
- Hardware
- On-site sparing and RMA handling
- Scope
- Our fleet or your own
Configured to the workload.
Three shapes cover most of what we deploy. Every one is delivered single-tenant, burned in, and acceptance tested before handover.
Training block
For pre-training and large-scale training runs that need tightly-coupled, high-density compute.
- Hardware
- H200 / B200 / B300-class HGX or NVL72 rack-scale
- Fabric
- InfiniBand or RoCEv2 non-blocking
- Density
- 30-130 kW per rack, liquid
- Managed layer
- Slurm, typically
Inference fleet
For serving models in production, where scale and uptime matter more than peak interconnect.
- Hardware
- H200 / MI300X-class, 141-192 GB
- Cooling
- Air or liquid
- Scale
- 64-1,024 GPUs
- Managed layer
- Kubernetes, typically
Fine-tuning cluster
For teams adapting existing models on a modest, air-cooled footprint with a shorter commitment.
- Hardware
- H100 / L40S-class, 8-128 GPUs
- Cooling
- Air-cooled friendly
- Managed layer
- Slurm or Kubernetes
256 H200-class GPUs on InfiniBand, managed Slurm, single-tenant Tier III hall.
Rack-scale NVL72 training block, liquid cooled, full O&M and fabric monitoring.
512-GPU inference fleet on managed Kubernetes with autoscaling node pools.
Illustrative configurations to gauge fit. Customer identities and pricing are never disclosed publicly.
Nothing is handed over untested.
A cluster that passes a smoke test is not a cluster that survives a three-week training run. Four stages, each with an artifact you receive.
DESIGNConfigured against the workload
Node count, GPU platform, fabric topology, storage throughput, power density, and the managed layer, sized to the jobs you actually intend to run. Written down before anything is ordered.
CONFIGURATION SHEET
DEPLOYMENT WINDOW
BUILDRacked, cabled, burned in
Hardware racked and cabled in a Tier III facility matched to your density and geography, then burned in under sustained load until the weak components fail here rather than in your first run.
BURN-IN REPORT
CABLING AND TOPOLOGY MAP
VALIDATEAcceptance tested end to end
NCCL all-reduce across the full cluster, per-link bandwidth and error counters, storage throughput, thermal soak, and scheduler smoke tests. You see the numbers before you accept the cluster.
NCCL / FABRIC RESULTS
ACCEPTANCE CRITERIA SIGN-OFF
OPERATERun, monitored, kept current
24/7 monitoring of GPUs, fabric, power, and thermals. Sparing and RMA handled on site, firmware and drivers kept on a tested track, and a named engineer who knows your cluster.
24/7 NOC AND SLA
MONTHLY HEALTH REPORT
This is what prevents silent throughput loss, mystery job failures, and the slow drift that turns a fast cluster into an average one.
Your cluster picks the building.
We deploy into independent Tier III facilities qualified for your specific cluster: your density, your geography, your term. Every facility clears the same bar before it carries a deployment.
Tier III
N+1
Density matched
Carrier-neutral
- Tier certification / design dossier
- REVIEWED
- Power headroom / N+1 topology
- REVIEWED
- Density and cooling limits
- DOCUMENTED
- Fiber providers and latency
- DOCUMENTED
- Remote hands and escalation path
- ON FILE
- Site walk
- BEFORE DEPLOYMENT
Facility detail shared under NDA / metros disclosed there
Weeks, not procurement quarters.
Requirements and configuration
One working session: workload, scale, density, interconnect, storage, term length, and the managed layer you want. You leave with a written configuration.
Quote and cluster spec
A configuration sheet with the numbers in it: node counts, fabric, storage, the managed layer, the SLA, and the deployment window. Every number is in the quote; none are on the website.
Build, validate, handover
Racked, burned in, and acceptance tested in a Tier III facility. Bare-metal access, your scheduler or ours, and a direct line to the engineers who stood it up. Newest-generation platforms depend on allocation timing, and we say so in the quote.
Single-tenant by default, so your workloads never share a hypervisor with strangers. Clusters run bare metal in facilities whose SOC 2 or ISO 27001 attestations we review during qualification and make available under NDA. Private networking, dedicated storage, and customer-controlled key material where the workload requires it.
Already own the hardware?
Owning GPUs is the easy part; keeping a fabric healthy at 3 a.m. is not. We take over operations for fleets you already own, deployment, scheduler, monitoring, sparing, firmware, and the on-call rotation, under an SLA, in your facility or one we qualify for you.
We bring our customers to your floor.
Crystal Cloud contracts with the end customer and deploys directly into your facility. Requirements run from 2 to 100 MW, single-tenant, Tier III, air and liquid. You get one credit-verified counterparty and a filled hall, not a stream of leads to chase.
Questions.
What does Crystal Cloud actually provide?
Enterprise GPU as a service: dedicated bare-metal GPU clusters with high-speed interconnect, plus the managed layer on top, Slurm, Kubernetes, or both, and 24/7 operations and maintenance. You get root access to your own hardware and an engineering team that runs it.
Is the hardware shared with other customers?
No. Clusters are single-tenant bare metal by default. No hypervisor, no noisy neighbours, no shared GPUs. The nodes, the fabric, and the storage are yours for the term.
How fast can a cluster be delivered?
Weeks, not procurement quarters. Design and configuration in week 0, build and burn-in through weeks 1 to 3, acceptance testing and handover after that. Newest-generation platforms depend on allocation timing, and we say so up front.
Why is there no pricing on the site?
Every cluster is configured to the workload, the density, and the term, so the numbers live in a written quote rather than on a webpage. Tell us the shape of the cluster and an engineer replies with a configuration and a deployment window.
Start with the cluster you need.
I need a cluster
CONFIGURATION AND WINDOW IN WRITING
I have hardware to run
24/7 NOC / SPARING / SLA
I have capacity
WE DEPLOY OUR CUSTOMERS DIRECTLY
contact@crystalcloud.ai / Los Angeles, CA