What buyers need to know
An 8 × B300 node has 2.3 TB of nominal GPU memory. NVLink/NVSwitch, CPU, RAM, NVMe, fabric, tenancy and delivery date are separate configuration decisions, not assumptions attached to the GPU name.
Plan dedicated B300 capacity for robotics, VLA, LLM training and sustained inference. Confirm the complete node, term and deployment window before activation.
No payment is required to submit a request.
An 8 × B300 node has 2.3 TB of nominal GPU memory. NVLink/NVSwitch, CPU, RAM, NVMe, fabric, tenancy and delivery date are separate configuration decisions, not assumptions attached to the GPU name.
| Configuration | Best for | Pricing |
|---|---|---|
| 8 × B300 dedicated node | Robotics, VLA, LLM training | Reserved quote |
| VM allocation | Scoped pilot where supported | Request availability |
| Bare metal | Custom runtime and dedicated tenancy | Request availability |
| Multi-node cluster | Large-scale distributed AI | Custom proposal |
Current capacity, complete configuration and total pricing are confirmed before activation.
One clear path from requirement to a deployable configuration.
Tell Arvica the workload, GPU count, region and start date.
Arvica confirms configuration, capacity and complete charges.
Run a pilot or proceed under a reserved-capacity agreement.
No. It is aggregate nominal GPU memory. Your framework and topology determine how model state is distributed.
State the preferred delivery model. Availability and the exact isolation model are confirmed in the proposal.
For a stable workload, compare 6–12 month reserved terms after a scoped pilot. The contract defines renewal and scale options.
Target timing requires a current capacity confirmation. Do not schedule a launch from a generic hardware roadmap.
Include framework, model, GPU count, deployment model, region, start date, duration and acceptance test.
Share the workload and Arvica will prepare deployable options for review.
Get Deployable Options Within 24 Hours →