Supercomputing — General Computing

Computing Services

Full-spectrum power for every AI workload. From multi-thousand GPU training clusters to elastic cloud instances — one platform, transparent pricing, global availability.

Overview

One Platform, Every Workload

OWS delivers the complete computing spectrum. Whether you're training a foundation model requiring thousands of GPUs or deploying a lightweight inference endpoint, our standardized, measurable, on-demand computing services have you covered. Deploy in any of our 60+ global regions, scale on demand, and pay only for what you use.

Product Lines

Two Engines of Computing Power

Supercomputing (HPC)

Maximum performance, zero compromise

Purpose-built for the most demanding AI workloads — large-scale model training, scientific simulation, genomics, and high-fidelity rendering. Bare metal GPU servers with RDMA interconnects deliver maximum throughput with zero virtualization overhead.

  • Multi-thousand GPU parallel training support
  • High-speed RDMA / InfiniBand interconnect
  • Dedicated resources — no noisy neighbors
  • Containerized (K8s) or bare metal deployment

General Computing

Elastic, cost-optimized, always available

Versatile cloud computing for inference deployment, data processing, web services, and development environments. Elastic cloud VMs and container instances that auto-scale based on demand — pay only for what you use.

  • Auto-scaling based on real-time demand
  • Multiple instance types for varied performance needs
  • Cost-optimized for production workloads
  • VM, container, and serverless deployment options
Hardware

Supported GPU & Compute Hardware

No vendor lock-in. Choose the right silicon for your workload.

N

NVIDIA H100

80GB HBM3 · 3.35 TB/s bandwidth · The gold standard for large model training

N

NVIDIA H200

141GB HBM3e · 4.8 TB/s bandwidth · Next-gen training and inference

N

NVIDIA A100

80GB HBM2e · Proven workhorse for training and inference at scale

A

AMD MI300X

192GB HBM3 · High-bandwidth alternative for large-scale AI workloads

I

Intel Xeon

Latest-gen scalable processors for CPU-bound data processing and general workloads

Custom Configurations

Need something specific? We configure custom clusters tailored to your exact requirements.

Features

Built for Production AI

Heterogeneous Architecture

NVIDIA, AMD, Intel, and emerging chip architectures — choose the best hardware for each workload without vendor lock-in.

Unified Console

Manage all compute resources — GPU clusters, VMs, containers — from a single control plane with real-time monitoring and cost tracking.

Flexible Billing

Hourly, monthly, or annual billing — match your budget and usage pattern. Pay-as-you-go for experiments, reserved pricing for steady workloads.

99.99% SLA

Enterprise-grade availability with dedicated support channels, proactive monitoring, and automatic failover across regions.

Rapid Provisioning

Resources available in minutes, not days. Self-service provisioning through the console or API ?get from configuration to running workload fast.

Global Availability

Deploy computing in any of our 60+ regions. Place your workloads close to your data, your users, or wherever compliance demands.

Pricing

Flexible Billing, Perfect Scaling

Subscription

Reserved resources at lower rates for predictable, steady-state workloads. Commit monthly or annually for the best per-unit pricing.

Popular

Pay-as-You-Go

Zero waste billing for spiky, experimental, or early-stage workloads. Auto-scale up and down; pay only for consumed resources.

Enterprise

Custom contracts for large-scale or long-term commitments. Dedicated account management, bespoke pricing, and priority support.

Getting Started

From Sign-Up to Running in Minutes

1

Sign Up

Create your OWS account and get $10 free credit instantly.

2

Configure

Select your compute type, GPU model, region, and deployment parameters.

3

Deploy

Provision resources in minutes through our console or API.

4

Scale

Scale up or down on demand. Add GPUs, switch regions, adjust in real time.

Use Cases

Real Workloads, Real Results

Training a 70B Model

GPU512× NVIDIA H100
InterconnectInfiniBand 400Gbps
StorageDistributed NVMe
Duration~3 weeks continuous

Enterprise-grade stability for long-running training jobs with checkpoint recovery and dedicated monitoring.

Real-Time Inference API

Throughput10K requests/sec
LatencyP95 < 100ms
ScalingAuto, multi-region
Availability99.99% SLA

Deploy inference endpoints close to your users with auto-scaling and cross-region failover for production reliability.

100TB Daily Data Pipeline

Data Volume100TB / day
ProcessingDistributed ETL
ComputeElastic CPU + GPU
StorageObject + Block

Process massive training datasets with elastic compute that scales to demand and costs nothing when idle.

Match Your AI Project with the Right Computing Power

From a single GPU for experimentation to thousand-card clusters for foundation model training ?we'll help you find the perfect fit.