HARDWARE REFERENCE72-GPU system
Grace Blackwell
Exact GPU variant, CPU, RAM and interconnect depend on the confirmed instance. Memory values are hardware references, not allocated resources.
Manufacturer specifications ↗PRICINGOn-demand prices are Arvica's live catalogue rates (USD per GPU-hour), shown at deploy time. Reserved and enterprise prices are set in an accepted Arvica proposal.
Request capacity proposal →CAPACITYRequest availability
Choose on-demand or reserved compute. Location, start time and access environment are confirmed before provisioning.
ARVICA PRICE / USDGB200 NVL72 · Arvica pricing
ON-DEMANDArvica's live catalogue rate in USD per GPU-hour, for the exact configuration and current availability, locked in a signed quote before payment.
RESERVED & ENTERPRISETerm, volume and dedicated-capacity prices are set in an accepted Arvica proposal. Configuration, region and delivery are confirmed in your proposal.
Availability confirmed before order acceptance. Taxes and additional services are confirmed before payment.
Choose around your workload
01When to choose this GPU
Consider this platform for distributed training or inference that benefits from a large NVLink domain. Start with the model parallelism strategy, dataset and expected utilisation.
02When to consider alternatives
Compare GB300 for Blackwell Ultra requirements. A B200 node may be easier to size when the workload does not need a full rack-scale allocation.
03Memory planning
The NVL72 design includes 72 Blackwell GPUs and 36 Grace CPUs. Distributed software must still manage memory placement and communication across devices.
04Interconnect and scale
Specify the NVLink domain, external network, storage throughput, liquid-cooling environment and acceptance tests together. An aggregate bandwidth figure is not per-GPU application bandwidth.
05Software compatibility
Grace uses Arm CPUs. Verify that containers, native libraries, monitoring agents and data tooling support the host architecture before migration.
NVIDIA hardware reference ↗ · Selection guidance is Arvica's assessment; validate it against your workload
FROM CONFIGURATION TO ACCESSPrepare your compute environment
Operating system & containers
Specify the OS, framework and container image version. Arvica confirms the driver and GPU compatibility before activation. A template name is not a software licence or a guaranteed preinstalled image.
SSH & private access
Save an SSH public key during configuration. Keep the private key on your own device. The verified deployment record provides the actual host and login user once access is ready.
Storage & checkpoints
Separate boot disk, datasets, model weights and checkpoints in your capacity plan. Confirm persistence, backup ownership, attachment rules and deletion behaviour before relying on a volume.
Network & data location
Confirm ingress, egress, public IP access and private networking where required. For regulated or location-sensitive data, specify the required region in advanced settings before submitting.
First connection checklist
Once Arvica supplies verified access, connect using your private key and the exact host/user shown in your instance. Then inspect the allocated GPUs and topology.
ssh -i ~/.ssh/your_key USER@HOST
nvidia-smi
nvidia-smi topo -m
Replace USER and HOST with your own deployment details. These commands inspect an existing machine; they do not provision one.
RESERVED / CLUSTERSNeed more capacity?
Define your GPU allocation, interconnect, storage, location and commitment. Arvica prepares a capacity proposal around the workload.
Request capacity ↗ Plan before benchmarking
Model fit and throughput depend on precision, software, batch size, context and system topology. Compare workload estimates rather than an unsupported tokens-per-second promise.
Training cost calculator →FAQ
How do I choose the GPU count?
Consider this platform for distributed training or inference that benefits from a large NVLink domain. Start with the model parallelism strategy, dataset and expected utilisation.
What should I check about memory?
The NVL72 design includes 72 Blackwell GPUs and 36 Grace CPUs. Distributed software must still manage memory placement and communication across devices.
What software should I prepare?
Grace uses Arm CPUs. Verify that containers, native libraries, monitoring agents and data tooling support the host architecture before migration.
What interconnect is included?
Specify the NVLink domain, external network, storage throughput, liquid-cooling environment and acceptance tests together. An aggregate bandwidth figure is not per-GPU application bandwidth.
Can I stop billing by shutting down the operating system?
Do not assume so. Resource allocation, storage and reserved commitments may continue billing. Check the contract and request the appropriate lifecycle action through support.
Is my data retained after termination?
Retention depends on the agreed storage configuration. Export data and confirm backup and volume retention before requesting termination.
Can I deploy immediately?
Current configurations enter Arvica capacity review. Running status is shown only after infrastructure is verified.
Is the live GPU-hour price my total cost?
Not necessarily. On-demand usage is billed at Arvica's live catalogue rate; storage, network, tax and service charges are itemised before you commit, and reserved or enterprise terms are set in your proposal.
Can I use a larger cluster?
Use the enterprise capacity path for multi-node networking and reserved allocations.
