GPUaaS for enterprise AI infrastructure
Access NVIDIA GPU infrastructure through bare metal, GPU passthrough, vGPU, and Kubernetes-based GPUaaS models while keeping enterprise AI workloads under Indonesian data residency expectations.
GPUaaS consumption models for enterprise AI
NVIDIA GPU options for AI, VDI, rendering, and HPC
Designed for secure AI infrastructure in Indonesia
Frequently asked questions
Which GPUaaS model should we choose?
Use bare metal for maximum isolation and performance, passthrough VMs for VM lifecycle control, vGPU for shared visual or VDI workloads, and Kubernetes GPUaaS for cloud-native AI platforms and model serving.
Can GPUaaS support sensitive or regulated workloads?
Yes, subject to final architecture. Data flows, administrator access, network boundaries, encryption, logging, backup, identity, and support responsibilities should be documented before production.
Is the calculator a final quotation?
No. The calculator is an indicative planning tool. Final pricing depends on capacity, contract duration, support model, availability, service scope, and commercial approval.