Predictable availability
Reserve capacity ahead of time when consistent access matters to production or long-running workloads.
INTERPRO GPU COMPUTE
GPU compute for
every scale.
Launch individual GPU instances when you need them. Secure predictable capacity when your workload demands dedicated scale.
1–8GPU instances
1–36+reserved commitments
Fixed or flexibleGPU capacity
H10080 GBGPU VRAM
B200180 GBGPU VRAM
01GPU INSTANCESFlexible GPU compute when you need it
02RESERVED CAPACITYPredictable capacity for ongoing workloads
01 / GPU INSTANCES
Start with the GPU.
Scale when you need to.
Choose a defined GPU configuration for training, inference, development, rendering, or AI applications. GPU Instances are flexible and usage-based, with no term commitment, making them a good fit for validating workloads, development, burst capacity, and workloads that do not require committed availability.
Request GPU Instance Quote →GPU INSTANCERFQ
GPUH100 / B200 / A100
COUNT1× / 2× / 4× / 8×
MEMORYGPU VRAM + configurable system RAM
STORAGENVMe options
BILLINGUsage-based / hourly reference rate
Best for validating workloads, development, burst capacity, and flexible usage. No term commitment is required, and duration alone does not turn an instance into Reserved Capacity.
02 / RESERVED CAPACITY
Reserve the capacity,
not just a GPU.
For production workloads and planned training runs, reserve capacity ahead of time when predictable availability, a dedicated configuration, or predictable long-running spend matters. Request a fixed GPU configuration—or let InterPro match available hardware that meets your minimum requirements.
Fixed or flexible GPU
Request a specific GPU model, or define minimum requirements and allow an equivalent NVIDIA configuration.
Planned commitment
Choose a commitment that matches your workload, with pricing quoted around capacity, availability, term, and volume.
Built for scale
Reserved Capacity can be scoped around GPU count, networking, region, timeline, and interconnected multi-node requirements.
Example request
Request Reserved Capacity →“16 GPUs, H100/H200 acceptable, 80+ GB VRAM, 960 GB RAM, US region, 12-month capacity commitment.”
GPU INSTANCES VS RESERVED CAPACITY
Choose based on
how you need compute.
Duration is not the deciding factor. The key difference is whether you need flexible usage or planned, predictable capacity.
Flexible compute when you need it.
Choose a defined GPU configuration and use it for hours, days, or longer. Best for validating workloads, development, inference, burst capacity, and situations where you do not need committed availability.
Predictable capacity for planned workloads.
Commit capacity ahead of time when availability, a dedicated configuration, predictable long-running spend, or multiple interconnected nodes matters.
03 / GPU PRICES
Published reference rates.
Reference hourly rates for selected GPU configurations. Final pricing may vary by configuration, availability, commitment and volume.
GPUREFERENCE RATE / HR
Reference rates shown for GPU instances. Reserved capacity and longer commitments are quoted based on requirements and availability.
01 / COMPUTE
Your GPU workload,
ready to run.
From selecting the right GPU to running your workload, InterPro helps simplify the infrastructure behind AI applications.
01
Choose your compute
Select the GPU configuration that fits your workload, from GPU Instances to Reserved Capacity.
02
Prepare your environment
Configure the software environment and infrastructure required for your workload.
03
Run your workload
Use your GPU infrastructure for AI training, fine-tuning, inference, generative AI and data processing.
04
Scale when you need it
Start with GPU Instances and move to Reserved Capacity as your workload grows.
OUR SERVICES
End-to-end data center
& GPU services.
Beyond compute capacity, InterPro supports the infrastructure around AI workloads—from rack deployment to high-speed networking and ongoing operations.
GPU Rental & Compute
On-demand instances and reserved capacity for AI workloads.
Server Rack & Deployment
Rack installation, server deployment and infrastructure integration.
Cluster & High-Speed Network Setup
High-speed networking and infrastructure support for AI compute environments.
Hardware Maintenance & On-site Support
Remote and on-site troubleshooting, replacement and lifecycle support.
Data Center Managed Services
Monitoring, incident management, spare-parts logistics and operations.
System & Software Support
Linux/Windows, Docker/Kubernetes, AI frameworks and virtualization.
Network Security & Access
Firewall, VLAN, VPN and access-control support.
Business Continuity & Disaster Recovery
Resilience planning and operational continuity for critical workloads.
REQUEST A QUOTE
Configure your
GPU compute.
Choose the GPU configuration that fits your workload. GPU Instances are flexible and usage-based; Reserved Capacity is designed for planned, predictable availability.
FAQs
Questions worth
answering clearly.
Find answers about GPU Instances, Reserved Capacity, and the infrastructure services around your AI workloads.
What can I launch on-demand?
The InterPro console shows the GPU instance types and configurations currently available to deploy. The catalog changes with capacity, so the console is the source of truth at launch time.
How is on-demand usage billed?
Compute is metered by the second and shown as an hourly rate. There is no term commitment for on-demand instances. Any additional service charges are shown separately in the console.
Can I rent an instance for a longer period?
Yes. A longer rental can remain a GPU Instance; duration alone does not turn it into Reserved Capacity. Longer commitments may qualify for lower rates.
When should I reserve capacity?
Reserved capacity is the better fit when you need guaranteed availability, a dedicated configuration, predictable long-running spend, or multiple interconnected nodes. If you are still validating the workload, start on-demand.
Can I request capacity without knowing the exact GPU model?
Yes. You can provide minimum requirements such as GPU count, VRAM, system RAM, storage, region, and commitment, and InterPro can recommend a configuration that meets them.
Can I specify a GPU model for Reserved Capacity?
Yes. You can request a specific GPU model, or allow an equivalent NVIDIA GPU that meets your minimum requirements.
How quickly can a dedicated deployment be scoped?
We aim to respond within one business day and return a written capacity plan after confirming the requirements. Provisioning time depends on the GPU type, quantity, region, and configuration.
Can you support multi-node GPU clusters?
Yes. We scope multi-node and dedicated deployments around GPU count, networking, region, timeline, and term.
What compliance requirements can you support?
InterPRO is not currently SOC 2 or HIPAA certified in its own name. Share any security, data residency, or compliance requirements at the start, and we will confirm what can be supported before proposing a deployment.
Do you provide data center and hardware support?
Yes. InterPro provides rack and deployment support, hardware maintenance, managed data center services, system and software support, and network security services.
NEED SOME GUIDANCE?
Not sure what
you need?
Tell us about your workload. If you are not sure which GPU, configuration or capacity is right, our team can help you determine the best starting point.