Verda vs QuantaCloud: GPU Compute Price Comparison
Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for Verda and QuantaCloud. 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
QuantaCloud provides bare-metal A100, H100, H200, and B300 GPU clusters with InfiniBand interconnect and no virtualization overhead, purpose-built for large-scale LLM training and multi-node distributed AI workloads. Reserved and cluster configurations are available for organizations that need dedicated GPU infrastructure with consistent performance for long-running training runs. A specialist bare-metal GPU cloud for AI labs and enterprises that need maximum cluster performance for frontier model training.
- Bare-metal performance
- InfiniBand networking
- Large cluster configs
- H200 and B300 availability
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.
QuantaCloud — bare-metal provider
QuantaCloud provides bare-metal A100, H100, H200, and B300 GPU clusters with InfiniBand interconnect and no virtualization overhead, purpose-built for large-scale LLM training and multi-node distributed AI workloads. Reserved and cluster configurations are available for organizations that need dedicated GPU infrastructure with consistent performance for long-running training runs. A specialist bare-metal GPU cloud for AI labs and enterprises that need maximum cluster performance for frontier model training.
Billing model comparison
Verda uses a On-demand, Reserved billing model with a minimum commitment of None. QuantaCloud uses Reserved / On-demand billing with a Varies by config 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. QuantaCloud is best suited for: Large-scale LLM training, Multi-node clusters, Reserved GPU capacity. Its key strengths are bare-metal performance, infiniband networking, large cluster configs. 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). QuantaCloud 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 QuantaCloud
Verda was founded in 2020 and is headquartered in Helsinki, Finland. QuantaCloud was founded in 2021 and is headquartered in United States. Verda has 1 years more operational history than QuantaCloud, 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.