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
Sesterce is a French GPU cloud offering one of the widest GPU selections in Europe — 26 GPU types including A30, A100, and H100 — across 11 EU regions, making it the broadest European GPU cloud for teams with diverse hardware requirements. On-demand and reserved billing options are available with competitive pricing for AI training, LLM fine-tuning, and inference workloads. A top choice for EU AI teams that need GPU variety and GDPR-compliant European data residency.
- 26 GPU types
- 11 regions
- EU-based infrastructure
- Competitive A30/A100 pricing
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.
Sesterce — specialist provider
Sesterce is a French GPU cloud offering one of the widest GPU selections in Europe — 26 GPU types including A30, A100, and H100 — across 11 EU regions, making it the broadest European GPU cloud for teams with diverse hardware requirements. On-demand and reserved billing options are available with competitive pricing for AI training, LLM fine-tuning, and inference workloads. A top choice for EU AI teams that need GPU variety and GDPR-compliant European data residency.
Billing model comparison
AWS uses a On-demand, Reserved (1yr/3yr), Spot billing model with a minimum commitment of None (on-demand). Sesterce 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 Sesterce'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. Sesterce is best suited for: EU AI teams, Wide GPU variety needs, Cost-sensitive European workloads. Its key strengths are 26 gpu types, 11 regions, eu-based infrastructure. As a hyperscaler, AWS offers broader ecosystem integration and compliance certifications at a premium price. Sesterce 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). Sesterce offers Standard → Enterprise support across 4 regions (EU-West, EU-Central, US and 1 more). 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 Sesterce
AWS was founded in 2006 and is headquartered in Seattle, WA. Sesterce was founded in 2018 and is headquartered in Marseille, France. AWS has 12 years more operational history than Sesterce, 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.