NVIDIA B200 GPU Australia — Cloud, Dedicated & Reserved
B200 brings Blackwell compute to demanding training and inference workloads. Compare complete server configurations, including usable memory and interconnect, before selecting a GPU count.
Request B200 in Australia and APAC as hourly Blackwell cloud GPUs where live capacity exists, a dedicated 8-GPU B200 node or reserved capacity for training, inference and fine-tuning. Published B200 platforms carry 180 GB or 192 GB HBM3e per GPU: the exact memory and specification are stated per configuration in your quote, not assumed from the model name. GPU cloud infrastructure in Australia · enterprise GPU clusters in Australia
On-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.
Choose on-demand or reserved compute. Location, start time and access environment are confirmed before provisioning.
AUSTRALIA & APAC / B200
B200 GPU compute for dedicated and enterprise workloads
Request B200 for on-demand evaluation, a dedicated 8-GPU node, reserved capacity or a multi-node enterprise cluster. Arvica confirms the exact system, Australia/APAC region, interconnect, storage, term, current capacity and pricing before commitment. Australia-based GPU capacity.
Choose B200 when the workload needs the Blackwell platform (fifth-generation NVLink, FP8/FP4 acceleration with a Blackwell-compatible stack) but fits within a 180–192 GB memory budget per GPU. Compare B300 when model state, activations or KV cache exceed that budget and fewer, larger GPUs lower the total cost; compare H200 when staying on the Hopper runtime avoids a migration. Dedicated 8-GPU B200 nodes and reserved B200 capacity are quoted as complete configurations for Australia and APAC.
Term, 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
01
When to choose this GPU
Evaluate B200 for workloads with a Blackwell-compatible software stack and a clear need for low-precision acceleration. Measure quality as well as throughput when changing precision.
02
When to consider alternatives
Compare B300 when memory headroom is the limiting factor. Compare H200 when keeping the existing Hopper runtime reduces migration effort and meets your service targets.
03
Memory planning
Published platform configurations list different B200 memory capacities. The catalogue range is 180–192 GB HBM3e; the accepted instance specification determines your allocation.
04
Interconnect and scale
Blackwell platforms can use fifth-generation NVLink. A GPU model name alone does not establish the number of linked GPUs, host CPU, network bandwidth or dedicated tenancy.
05
Software compatibility
Use framework builds and CUDA extensions explicitly supporting Blackwell. Confirm container architecture and driver requirements before migrating an existing image.
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.
Replace USER and HOST with your own deployment details. These commands inspect an existing machine; they do not provision one.
Size the job before committing
Model memory
Parameter count × bytes per weight estimates weights only. Add KV cache, activations, temporary tensors and framework overhead. Training additionally needs gradients and optimiser state.
Measure useful throughput
Record model version, precision, input/output length, concurrency, latency and error rate together. Compare the cost of a completed job or successful request under the same conditions.
Complete cost
Include all allocated GPUs, runtime, storage, networking, taxes and support. Monthly projections use 730 hours for comparison; your contract defines the billable period and minimum term.
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.
Use B200 when the model fits a 180–192 GB per-GPU memory budget and you want the Blackwell platform. Move to B300 (288 GB HBM3e) when memory headroom is the limiting factor, or when fewer larger GPUs reduce the cost of a measured workload.
Can I reserve B200 GPUs in Australia?
Yes. Request a dedicated 8-GPU B200 node or reserved B200 capacity with the required location, term and start date. The memory variant, configuration, location and pricing are confirmed in a written proposal.
How do I choose the GPU count?
Evaluate B200 for workloads with a Blackwell-compatible software stack and a clear need for low-precision acceleration. Measure quality as well as throughput when changing precision.
What should I check about memory?
Published platform configurations list different B200 memory capacities. The catalogue range is 180–192 GB HBM3e; the accepted instance specification determines your allocation.
What software should I prepare?
Use framework builds and CUDA extensions explicitly supporting Blackwell. Confirm container architecture and driver requirements before migrating an existing image.
What interconnect is included?
Blackwell platforms can use fifth-generation NVLink. A GPU model name alone does not establish the number of linked GPUs, host CPU, network bandwidth or dedicated tenancy.
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.
Evaluate B200 for workloads with a Blackwell-compatible software stack and a clear need for low-precision acceleration. Measure quality as well as throughput when changing precision.
Test H200 when model weights, KV cache and concurrent requests compete for memory. Extra capacity can reduce the need to split a workload across GPUs, depending on precision and runtime overhead.
Evaluate B300 when model state, activations or KV cache constrain your current deployment. Use a representative model and concurrency target to decide whether fewer larger GPUs improve total cost.
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 changes between configurations
Configuration
Practical difference
Confirm before ordering
SXM · VM · 180–192 GB HBM3e
Guest OS and assigned resources within a virtual machine
GPU count, NVLink/NVSwitch topology, inter-node fabric and NUMA placement
SXM · Bare Metal · 180–192 GB HBM3e
Dedicated physical host configuration; host access follows the confirmed service
GPU count, NVLink/NVSwitch topology, inter-node fabric and NUMA placement
Size the working set
Weights alone are approximately parameters × bytes per parameter. A 7B model at BF16 needs about 14 GB just for weights; a 70B model about 140 GB. Add KV cache, activations, framework buffers and training state. These are arithmetic estimates, not fit guarantees.
Measure useful performance
Compare the same model revision, precision, sequence length and concurrency. Record time to first token, p95 latency, output tokens/s, peak memory and full instance cost. Training comparisons should include step time and convergence at the same quality target.
Evidence status
Manufacturer specifications are linked below. No Arvica application-throughput benchmark is published for this configuration yet. Request a workload-specific acceptance test before making performance commitments.
Configure dedicated PCIe / SXM, virtual-machine and bare-metal capacity with Arvica. Submit your requirements for a deployment proposal.
Request your preferred configuration. Host sizes are illustrative; the written proposal confirms capacity, location, final pricing and delivery. Submitting an enquiry is free and does not reserve capacity.
2 configurations available for enquiry
Capacity confirmation requiredVirtual machine
B200 SXM
Price in your proposalYour configuration and term are priced in an Arvica proposal. Delivery schedule confirmed in proposal.
Illustrative configuration
GPU
1 × B200
GPU memory
180–192 GB HBM3e
vCPU
16
RAM
128 GB
Storage
500 GB
AvailabilityConfirmation requiredRegionConfirm in proposalServiceArvica Cloud
