Crusoe Cloud vs Atlas Cloud: GPU Compute Price Comparison
Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for Crusoe Cloud and Atlas Cloud. Updated July 2026.
Provider Overview
Strengths & Best For
Crusoe Cloud powers H100 SXM5 and B200 GPU instances using stranded and renewable energy sources, making it one of the few carbon-negative on-demand GPU cloud providers in the US. Competitive pricing on H100 clusters for AI training and LLM fine-tuning, with a mission to reduce the carbon footprint of large-scale compute. An ideal choice for ESG-conscious enterprises and AI labs that want high-performance hardware without the environmental cost.
- Clean energy compute
- Competitive H100 pricing
- B200 availability
- Carbon-negative mission
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
Crusoe Cloud — specialist provider
Crusoe Cloud powers H100 SXM5 and B200 GPU instances using stranded and renewable energy sources, making it one of the few carbon-negative on-demand GPU cloud providers in the US. Competitive pricing on H100 clusters for AI training and LLM fine-tuning, with a mission to reduce the carbon footprint of large-scale compute. An ideal choice for ESG-conscious enterprises and AI labs that want high-performance hardware without the environmental cost.
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
Crusoe Cloud uses a On-demand, Reserved 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
Crusoe Cloud is best suited for: Sustainability-focused teams, Large-scale AI training, ESG-conscious enterprises. Its key strengths are clean energy compute, competitive h100 pricing, b200 availability. 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
Crusoe Cloud offers Standard → Enterprise support across 2 regions (US-West, US-Central). Atlas Cloud offers Standard support across 1 region (IS). Crusoe Cloud's broader region footprint gives it an advantage for latency-sensitive workloads or teams with data residency requirements in specific geographies.
Provider background: Crusoe Cloud vs Atlas Cloud
Crusoe Cloud was founded in 2018 and is headquartered in San Francisco, CA. Atlas Cloud was founded in 2022 and is headquartered in Reykjavik, Iceland. Crusoe Cloud has 4 years more operational history than Atlas Cloud, 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.