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
Verda (formerly DataCrunch) is a Finnish GPU cloud offering 13 GPU types including H100, A100, RTX A6000, and V100 instances with competitive on-demand pricing and enterprise-grade infrastructure for AI and ML workloads. On-demand and reserved billing options are available from Finnish data centers, providing EU data residency for Nordic and European teams with GDPR requirements. A reliable European GPU cloud for cost-sensitive AI training and inference with broad hardware variety.
- Finnish infrastructure
- Competitive V100/A100 pricing
- 13 GPU types
- Enterprise-grade
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.
Verda — specialist provider
Verda (formerly DataCrunch) is a Finnish GPU cloud offering 13 GPU types including H100, A100, RTX A6000, and V100 instances with competitive on-demand pricing and enterprise-grade infrastructure for AI and ML workloads. On-demand and reserved billing options are available from Finnish data centers, providing EU data residency for Nordic and European teams with GDPR requirements. A reliable European GPU cloud for cost-sensitive AI training and inference with broad hardware variety.
Billing model comparison
AWS uses a On-demand, Reserved (1yr/3yr), Spot billing model with a minimum commitment of None (on-demand). Verda 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 Verda'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. Verda is best suited for: EU AI teams, Cost-sensitive training, Nordic data residency. Its key strengths are finnish infrastructure, competitive v100/a100 pricing, 13 gpu types. As a hyperscaler, AWS offers broader ecosystem integration and compliance certifications at a premium price. Verda 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). Verda offers Standard → Enterprise support across 2 regions (EU-North, 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 Verda
AWS was founded in 2006 and is headquartered in Seattle, WA. Verda was founded in 2020 and is headquartered in Helsinki, Finland. AWS has 14 years more operational history than Verda, 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.