RTX 5090 offers Blackwell with 32 GB GDDR7. Explore it for model development, image workloads and inference that fit within the available memory.
Blackwell
Exact GPU variant, CPU, RAM and interconnect depend on the confirmed instance. Memory values are hardware references, not allocated resources.
Manufacturer specifications ↗Public reference / GPU-hour. Arvica sell price, taxes and additional services require an approved quote.
Choose on-demand or reserved compute. Location, start time and access environment are confirmed before provisioning.
| Published source | GPU variant | Reference / GPU-hour | Price basis |
|---|---|---|---|
| No comparable published rate is currently recorded for this configuration. Request a configuration-specific quote. | |||
Published reference rates do not establish live availability or identical instance specifications. Your Arvica quote confirms the complete configuration and charges.
Evaluate a single GPU for prototypes and bounded inference jobs. Measure the chosen model, quantisation and concurrency instead of assuming suitability from the generation name.
Compare RTX 4090 for the same workload when 24 GB fits. Compare RTX 6000 Ada or RTX PRO 6000 Server when additional memory or a professional GPU configuration is required.
The standard RTX 5090 specification is 32 GB GDDR7. Regional or differently named variants must be checked separately. Leave room for runtime overhead.
Confirm GPU passthrough, PCIe layout and resource isolation in the offered server. Do not infer an NVLink training fabric or enterprise SLA from this GPU model.
Use a Blackwell-compatible CUDA and framework build. Confirm that your application's licences and hosting terms support the intended deployment.
NVIDIA hardware reference ↗ · Selection guidance is Arvica's assessment; validate it against your workload
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.
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.
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.
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.
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.
Parameter count × bytes per weight estimates weights only. Add KV cache, activations, temporary tensors and framework overhead. Training additionally needs gradients and optimiser state.
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.
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.
Define your GPU allocation, interconnect, storage, location and commitment. Arvica prepares a capacity proposal around the workload.
Request capacity ↗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 →Evaluate a single GPU for prototypes and bounded inference jobs. Measure the chosen model, quantisation and concurrency instead of assuming suitability from the generation name.
The standard RTX 5090 specification is 32 GB GDDR7. Regional or differently named variants must be checked separately. Leave room for runtime overhead.
Use a Blackwell-compatible CUDA and framework build. Confirm that your application's licences and hosting terms support the intended deployment.
Confirm GPU passthrough, PCIe layout and resource isolation in the offered server. Do not infer an NVLink training fabric or enterprise SLA from this GPU model.
Do not assume so. Resource allocation, storage and reserved commitments may continue billing. Check the contract and request the appropriate lifecycle action through support.
Retention depends on the agreed storage configuration. Export data and confirm backup and volume retention before requesting termination.
Current configurations enter Arvica capacity review. Running status is shown only after infrastructure is verified.
No. Your quote defines GPU, storage, network, tax and service charges before you commit.
Use the enterprise capacity path for multi-node networking and reserved allocations.
Explore PCIe / SXM and virtual machine / bare-metal configurations. Reserve with Arvica before activation.
2 configurations for enquiry
