Planned

GPU-accelerated compute for AI and beyond

Planned GPU workflows for machine learning, AI inference, rendering, and scientific computing. Hardware tiers and multi-GPU support will be confirmed before availability.

Key features

GPU Configurations

GPU tiers and availability will be published before GPU Cloud launch.

Multi-GPU Scope

Multi-GPU configurations are part of the intended product scope.

Pre-built Environments

CUDA, PyTorch, TensorFlow, and other image support will be confirmed before launch.

Interconnect

GPU interconnect details will be published with the hardware specification.

Persistent Storage

Storage attachment workflows will be documented before availability.

Jupyter Integration

Jupyter workflows are part of the planned GPU development experience.

Why choose this product

Flexible Access

The planned service is intended to provide GPU access without hardware procurement.

Experimentation

GPU workflows are intended to support iterative model development.

Resource Scaling

Scaling behavior will be published with the GPU launch specification.

Launch Pricing

GPU billing terms will be confirmed before availability.

Technical specifications

GPU Memory16 – 80 GB per GPU
System RAMUp to 240 GB
vCPUsUp to 48 cores
StorageUp to 2 TB NVMe
InterconnectHigh-bandwidth GPU link
FrameworksCUDA, PyTorch, TensorFlow

Pricing

Transparent pricing with no hidden fees.

Planned rollout

Pricing will be published when this product enters the infrastructure rollout. VPS Hosting is the initial commercial launch product.

Use cases

Model Training

Train deep learning models on high-performance GPU hardware.

AI Inference

Planned GPU configurations for real-time or batch inference workloads.

LLM Fine-Tuning

Fine-tune large language models on high-memory GPU instances.

3D Rendering

GPU-accelerated rendering for animation, visualization, and CAD.

Video Encoding

Hardware-accelerated video transcoding and processing pipelines.

Scientific Computing

Computational physics, chemistry, and genomics simulations.

Frequently asked questions

GPU tiers and supported hardware will be published before GPU Cloud availability.

Multi-GPU support is part of the intended product scope and will be confirmed before launch.

Supported images and framework versions will be published with the launch specification.

GPU billing terms will be published before provisioning opens.

Storage attachment support will be documented before GPU Cloud availability.

Jupyter support is part of the planned GPU development workflow.

Explore GPU Cloud capabilities

Review the planned GPU compute scope for AI, ML, and high-performance workloads.