TensorDock vs Oblivus: GPU Compute Price Comparison
Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for TensorDock and Oblivus. 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
Oblivus offers H100 and A100 GPU instances on-demand at competitive rates with straightforward pricing and no hidden fees, making it an accessible option for AI training and inference workloads on a budget. Spot GPU rental is also available for further cost savings on interruptible jobs. A no-frills GPU cloud for startups and developers who want simple, transparent pricing without enterprise complexity.
- Low prices
- Simple pricing
- No hidden fees
- H100 availability
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.
Oblivus — specialist provider
Oblivus offers H100 and A100 GPU instances on-demand at competitive rates with straightforward pricing and no hidden fees, making it an accessible option for AI training and inference workloads on a budget. Spot GPU rental is also available for further cost savings on interruptible jobs. A no-frills GPU cloud for startups and developers who want simple, transparent pricing without enterprise complexity.
Billing model comparison
TensorDock uses a On-demand, Spot billing model with a minimum commitment of None. Oblivus uses On-demand, Spot 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. Oblivus is best suited for: Cost-sensitive training, Budget AI workloads, Startups. Its key strengths are low prices, simple pricing, no hidden fees. 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). Oblivus offers Community → Standard support across 2 regions (EU, US). 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 Oblivus
TensorDock was founded in 2020 and is headquartered in Boston, MA. Oblivus was founded in 2022 and is headquartered in Europe. TensorDock has 2 years more operational history than Oblivus, 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.