TensorDock vs Leafcloud: GPU Compute Price Comparison
Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for TensorDock and Leafcloud. Updated July 2026.
Provider Overview
Strengths & Best For
TensorDock offers H100, A100, RTX 4090, and RTX 3090 GPU instances across a distributed network of data centers at some of the most competitive on-demand and spot GPU rental prices available. Both on-demand and spot options are available, making it a popular budget AI training platform for cost-sensitive teams and researchers. A practical choice for LLM fine-tuning and batch inference workloads where price-per-GPU-hour is the primary concern.
- Very low prices
- Wide GPU variety
- Spot instances
- Global locations
Leafcloud is a Dutch sustainable cloud provider that reuses server waste heat to warm buildings, offering GPU compute with 100% renewable energy and GDPR-compliant EU data residency for environmentally conscious AI teams. On-demand billing and a strong sustainability mission make it one of the most genuinely green GPU cloud options in Europe. A top choice for Dutch and EU-based organizations that want to minimize the environmental impact of their AI training and inference workloads.
- Waste heat reuse
- Sustainable compute
- GDPR compliant
- Dutch presence
Live GPU Pricing
Region Coverage
Popular Comparisons
TensorDock — specialist provider
TensorDock offers H100, A100, RTX 4090, and RTX 3090 GPU instances across a distributed network of data centers at some of the most competitive on-demand and spot GPU rental prices available. Both on-demand and spot options are available, making it a popular budget AI training platform for cost-sensitive teams and researchers. A practical choice for LLM fine-tuning and batch inference workloads where price-per-GPU-hour is the primary concern.
Leafcloud — specialist provider
Leafcloud is a Dutch sustainable cloud provider that reuses server waste heat to warm buildings, offering GPU compute with 100% renewable energy and GDPR-compliant EU data residency for environmentally conscious AI teams. On-demand billing and a strong sustainability mission make it one of the most genuinely green GPU cloud options in Europe. A top choice for Dutch and EU-based organizations that want to minimize the environmental impact of their AI training and inference workloads.
Billing model comparison
TensorDock uses a On-demand, Spot billing model with a minimum commitment of None. Leafcloud 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
TensorDock is best suited for: Budget ML training, Batch inference, Cost-sensitive teams. Its key strengths are very low prices, wide gpu variety, spot instances. Leafcloud is best suited for: Sustainability-focused teams, European AI workloads, GDPR-sensitive data. Its key strengths are waste heat reuse, sustainable compute, gdpr compliant. 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
TensorDock offers Community → Pro support across 4 regions (US, EU, APAC and 1 more). Leafcloud offers Standard support across 2 regions (NL, EU). TensorDock's broader region footprint gives it an advantage for latency-sensitive workloads or teams with data residency requirements in specific geographies.
Provider background: TensorDock vs Leafcloud
TensorDock was founded in 2020 and is headquartered in Boston, MA. Leafcloud was founded in 2019 and is headquartered in Amsterdam, Netherlands. Leafcloud has 1 years more operational history than TensorDock, 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.