AWS vs Hyperstack: GPU Compute Price Comparison
Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for AWS and Hyperstack. Updated July 2026.
Provider Overview
Strengths & Best For
AWS offers on-demand, reserved, and spot GPU instances across EC2 P4d (A100), P5 (H100), and G6 (L40S) families, spanning 30+ global regions with enterprise SLAs and deep ML tooling via SageMaker. H100 and A100 clusters are available with InfiniBand networking for distributed LLM training and large-scale AI inference. The broadest ecosystem of any GPU cloud provider, making it the default choice for enterprises already invested in the AWS stack.
- Widest global region coverage
- Deep ecosystem integrations
- Enterprise SLAs
- Reserved instance discounts
Hyperstack provides NVIDIA-certified H100, A100, and RTX 4090 GPU instances with enterprise-grade support and high availability across US and EU regions. On-demand and reserved billing options are available, making it a reliable on-demand GPU cloud for enterprise AI teams that need certified hardware configurations and responsive support. A strong alternative to hyperscalers for production LLM inference and AI training workloads.
- NVIDIA-certified
- High availability
- EU/US coverage
- Strong support
Live GPU Pricing
Region Coverage
Popular Comparisons
AWS — hyperscaler provider
AWS offers on-demand, reserved, and spot GPU instances across EC2 P4d (A100), P5 (H100), and G6 (L40S) families, spanning 30+ global regions with enterprise SLAs and deep ML tooling via SageMaker. H100 and A100 clusters are available with InfiniBand networking for distributed LLM training and large-scale AI inference. The broadest ecosystem of any GPU cloud provider, making it the default choice for enterprises already invested in the AWS stack.
Hyperstack — specialist provider
Hyperstack provides NVIDIA-certified H100, A100, and RTX 4090 GPU instances with enterprise-grade support and high availability across US and EU regions. On-demand and reserved billing options are available, making it a reliable on-demand GPU cloud for enterprise AI teams that need certified hardware configurations and responsive support. A strong alternative to hyperscalers for production LLM inference and AI training workloads.
Billing model comparison
AWS uses a On-demand, Reserved (1yr/3yr), Spot billing model with a minimum commitment of None (on-demand). Hyperstack uses On-demand, Reserved billing with a None minimum. AWS's no-commitment on-demand model is more flexible for short-term or experimental workloads, while Hyperstack's commitment requirement suits teams with predictable long-running jobs.
Which workloads each provider suits best
AWS is best suited for: Enterprise workloads, Production ML inference, Teams already on AWS. Its key strengths are widest global region coverage, deep ecosystem integrations, enterprise slas. Hyperstack is best suited for: Enterprise AI, NVIDIA ecosystem users, Production inference. Its key strengths are nvidia-certified, high availability, eu/us coverage. As a hyperscaler, AWS offers broader ecosystem integration and compliance certifications at a premium price. Hyperstack as a specialist provider typically offers lower per-GPU rates for teams that don't need the full hyperscaler ecosystem.
Support tiers and region coverage
AWS offers Basic → Enterprise support across 5 regions (us-east-1, us-west-2, eu-west-1 and 2 more). Hyperstack offers Standard → Enterprise support across 2 regions (US-East, EU-West). AWS's broader region footprint gives it an advantage for latency-sensitive workloads or teams with data residency requirements in specific geographies.
Provider background: AWS vs Hyperstack
AWS was founded in 2006 and is headquartered in Seattle, WA. Hyperstack was founded in 2022 and is headquartered in London, UK. AWS has 16 years more operational history than Hyperstack, which may matter for teams evaluating provider stability and long-term contract risk. Use the live pricing table above to compare current on-demand and spot rates for specific GPU models, and the region map to verify coverage in your target geography.