Google Cloud vs UpCloud: GPU Compute Price Comparison
Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for Google Cloud and UpCloud. Updated July 2026.
Provider Overview
Strengths & Best For
Google Cloud provides A100 and H100 GPU instances via Compute Engine and Vertex AI, with sustained use discounts and committed use contracts that can significantly cut hourly GPU rental costs. TPU v4 and v5 accelerators are also available for TensorFlow and JAX workloads, giving teams a unique alternative to NVIDIA hardware. Spanning 30+ regions, it is the top choice for ML pipelines deeply integrated with the TensorFlow and Google ecosystem.
- Sustained use discounts
- Vertex AI integration
- TPU availability
- Strong networking
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
Google Cloud — hyperscaler provider
Google Cloud provides A100 and H100 GPU instances via Compute Engine and Vertex AI, with sustained use discounts and committed use contracts that can significantly cut hourly GPU rental costs. TPU v4 and v5 accelerators are also available for TensorFlow and JAX workloads, giving teams a unique alternative to NVIDIA hardware. Spanning 30+ regions, it is the top choice for ML pipelines deeply integrated with the TensorFlow and Google ecosystem.
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
Google Cloud uses a On-demand, Committed Use (1yr/3yr), Spot/Preemptible billing model with a minimum commitment of None (on-demand). UpCloud uses On-demand billing with a None minimum. Google Cloud's no-commitment on-demand model is more flexible for short-term or experimental workloads, while UpCloud's commitment requirement suits teams with predictable long-running jobs.
Which workloads each provider suits best
Google Cloud is best suited for: ML training pipelines, TensorFlow workloads, Teams using GCP services. Its key strengths are sustained use discounts, vertex ai integration, tpu availability. UpCloud is best suited for: European teams, Storage-intensive AI, Reliable inference. Its key strengths are maxiops storage, reliable uptime, european presence. As a hyperscaler, Google Cloud offers broader ecosystem integration and compliance certifications at a premium price. UpCloud as a specialist provider typically offers lower per-GPU rates for teams that don't need the full hyperscaler ecosystem.
Support tiers and region coverage
Google Cloud offers Basic → Premium support across 5 regions (us-central1, us-east4, europe-west4 and 2 more). UpCloud offers Standard support across 4 regions (FI, EU, US and 1 more). Google Cloud's broader region footprint gives it an advantage for latency-sensitive workloads or teams with data residency requirements in specific geographies.
Provider background: Google Cloud vs UpCloud
Google Cloud was founded in 2008 and is headquartered in Sunnyvale, CA. UpCloud was founded in 2011 and is headquartered in Helsinki, Finland. Google Cloud has 3 years more operational history than UpCloud, 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.