DataVolt vs QuantaCloud: GPU Compute Price Comparison
Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for DataVolt and QuantaCloud. Updated July 2026.
Provider Overview
Strengths & Best For
DataVolt is a European GPU cloud offering H100, H200, A100, and L40S instances with competitive on-demand and spot GPU rental pricing, full EU data residency, and straightforward access for AI and ML workloads. Spot availability makes it a cost-effective option for interruptible LLM training and fine-tuning jobs, while on-demand instances suit production inference. A practical European GPU cloud for teams that need GDPR-compliant infrastructure with flexible billing.
- Competitive H100/H200 pricing
- Spot availability
- EU data residency
- Simple pricing
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
DataVolt — specialist provider
DataVolt is a European GPU cloud offering H100, H200, A100, and L40S instances with competitive on-demand and spot GPU rental pricing, full EU data residency, and straightforward access for AI and ML workloads. Spot availability makes it a cost-effective option for interruptible LLM training and fine-tuning jobs, while on-demand instances suit production inference. A practical European GPU cloud for teams that need GDPR-compliant infrastructure with flexible billing.
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
DataVolt uses a On-demand, Spot 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
DataVolt is best suited for: EU AI teams, Cost-sensitive H100 workloads, Spot-tolerant training. Its key strengths are competitive h100/h200 pricing, spot availability, eu data residency. 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
DataVolt offers Community → Standard support across 1 region (EU). QuantaCloud offers Standard → Enterprise support across 1 region (US). Both providers have comparable region coverage — choose based on which specific regions overlap with your user base or data residency requirements.
Provider background: DataVolt vs QuantaCloud
DataVolt was founded in 2023 and is headquartered in Europe. QuantaCloud was founded in 2021 and is headquartered in United States. QuantaCloud has 2 years more operational history than DataVolt, 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.