Verda vs Cirrascale: GPU Compute Price Comparison
Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for Verda and Cirrascale. Updated July 2026.
Provider Overview
Strengths & Best For
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
Cirrascale Cloud Services provides enterprise-grade AI infrastructure featuring H100 NVL, H100 SXM5, and H200 GPU clusters with InfiniBand networking for high-throughput distributed LLM training and large-scale AI workloads. Dedicated cluster deployments and reserved configurations give enterprises full control over their GPU infrastructure without shared-tenancy concerns. A specialist provider for AI labs and enterprises that need dedicated H100 or H200 cluster capacity at scale.
- H100/H200 cluster focus
- InfiniBand networking
- Dedicated deployments
- Enterprise SLAs
Live GPU Pricing
Region Coverage
Popular Comparisons
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.
Cirrascale — specialist provider
Cirrascale Cloud Services provides enterprise-grade AI infrastructure featuring H100 NVL, H100 SXM5, and H200 GPU clusters with InfiniBand networking for high-throughput distributed LLM training and large-scale AI workloads. Dedicated cluster deployments and reserved configurations give enterprises full control over their GPU infrastructure without shared-tenancy concerns. A specialist provider for AI labs and enterprises that need dedicated H100 or H200 cluster capacity at scale.
Billing model comparison
Verda uses a On-demand, Reserved billing model with a minimum commitment of None. Cirrascale uses On-demand, Reserved billing with a None minimum. Both providers offer flexible billing options — compare the live pricing table above to find the best rate for your specific GPU model and workload duration.
Which workloads each provider suits best
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. Cirrascale is best suited for: Large-scale AI training, Enterprise LLM workloads, Dedicated cluster users. Its key strengths are h100/h200 cluster focus, infiniband networking, dedicated deployments. Both providers target similar workload profiles — the live pricing table above is the most reliable way to determine which offers better value for your specific GPU model and region requirements.
Support tiers and region coverage
Verda offers Standard → Enterprise support across 2 regions (EU-North, EU-West). Cirrascale offers Standard → Enterprise support across 1 region (US). Verda's broader region footprint gives it an advantage for latency-sensitive workloads or teams with data residency requirements in specific geographies.
Provider background: Verda vs Cirrascale
Verda was founded in 2020 and is headquartered in Helsinki, Finland. Cirrascale was founded in 2009 and is headquartered in San Diego, CA. Cirrascale has 11 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.