DataVolt vs Atlas Cloud: GPU Compute Price Comparison
Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for DataVolt and Atlas Cloud. 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
Atlas Cloud is an Iceland-based GPU cloud offering H100 and A100 instances powered by 100% renewable geothermal energy, combining high-performance AI compute with a genuinely carbon-neutral infrastructure footprint. Competitive on-demand pricing and low-latency connectivity to Europe make it an attractive sustainable GPU cloud for EU-based AI training and inference workloads. A top choice for sustainability-focused teams that want green GPU compute without sacrificing performance.
- 100% renewable energy
- Competitive H100 pricing
- Low latency to Europe
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.
Atlas Cloud — specialist provider
Atlas Cloud is an Iceland-based GPU cloud offering H100 and A100 instances powered by 100% renewable geothermal energy, combining high-performance AI compute with a genuinely carbon-neutral infrastructure footprint. Competitive on-demand pricing and low-latency connectivity to Europe make it an attractive sustainable GPU cloud for EU-based AI training and inference workloads. A top choice for sustainability-focused teams that want green GPU compute without sacrificing performance.
Billing model comparison
DataVolt uses a On-demand, Spot billing model with a minimum commitment of None. Atlas Cloud uses On-demand 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
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. Atlas Cloud is best suited for: Sustainability-focused teams, European AI workloads, Training runs. Its key strengths are 100% renewable energy, competitive h100 pricing, low latency to europe. 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). Atlas Cloud offers Standard support across 1 region (IS). 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 Atlas Cloud
DataVolt was founded in 2023 and is headquartered in Europe. Atlas Cloud was founded in 2022 and is headquartered in Reykjavik, Iceland. Atlas Cloud has 1 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.