Paperspace vs UpCloud: GPU Compute Price Comparison
Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for Paperspace and UpCloud. Updated July 2026.
Provider Overview
Strengths & Best For
Paperspace (now part of DigitalOcean) offers A100, RTX 4000 ADA, and RTX 5000 ADA GPU instances alongside Gradient, its managed ML platform with Jupyter notebooks, experiment tracking, and one-click model deployment. On-demand and monthly billing options make it accessible for individuals and small teams exploring AI training and fine-tuning without complex infrastructure setup. A beginner-friendly on-demand GPU cloud with a polished notebook-centric experience.
- Managed ML platform
- Jupyter notebooks
- Simple UI
- DigitalOcean integration
UpCloud is a Finnish cloud provider known for its MaxIOPS storage and reliable infrastructure, now offering H100 and A100 GPU instances for AI and ML workloads across Finnish, EU, US, and APAC data centers. On-demand billing and a strong uptime track record make it a dependable choice for European teams that need GPU compute paired with high-performance storage for data-intensive AI training pipelines. A solid European GPU cloud for teams that value reliability and storage performance alongside GPU compute.
- MaxIOPS storage
- Reliable uptime
- European presence
- Competitive pricing
Live GPU Pricing
Region Coverage
Popular Comparisons
Paperspace — specialist provider
Paperspace (now part of DigitalOcean) offers A100, RTX 4000 ADA, and RTX 5000 ADA GPU instances alongside Gradient, its managed ML platform with Jupyter notebooks, experiment tracking, and one-click model deployment. On-demand and monthly billing options make it accessible for individuals and small teams exploring AI training and fine-tuning without complex infrastructure setup. A beginner-friendly on-demand GPU cloud with a polished notebook-centric experience.
UpCloud — specialist provider
UpCloud is a Finnish cloud provider known for its MaxIOPS storage and reliable infrastructure, now offering H100 and A100 GPU instances for AI and ML workloads across Finnish, EU, US, and APAC data centers. On-demand billing and a strong uptime track record make it a dependable choice for European teams that need GPU compute paired with high-performance storage for data-intensive AI training pipelines. A solid European GPU cloud for teams that value reliability and storage performance alongside GPU compute.
Billing model comparison
Paperspace uses a On-demand, Monthly billing model with a minimum commitment of None. UpCloud 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
Paperspace is best suited for: ML beginners, Notebook-based workflows, Small teams. Its key strengths are managed ml platform, jupyter notebooks, simple ui. UpCloud is best suited for: European teams, Storage-intensive AI, Reliable inference. Its key strengths are maxiops storage, reliable uptime, european presence. 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
Paperspace offers Community → Growth support across 3 regions (US-East, US-West, EU-West). UpCloud offers Standard support across 4 regions (FI, EU, US and 1 more). UpCloud's broader region footprint gives it an advantage for latency-sensitive workloads or teams with data residency requirements in specific geographies.
Provider background: Paperspace vs UpCloud
Paperspace was founded in 2014 and is headquartered in New York, NY. UpCloud was founded in 2011 and is headquartered in Helsinki, Finland. UpCloud has 3 years more operational history than Paperspace, 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.