TensorDock vs Vast.ai: GPU Compute Price Comparison
Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for TensorDock and Vast.ai. 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
Vast.ai is a peer-to-peer GPU marketplace listing 10,000+ GPUs — including H100, A100, and RTX 4090 — from hosts worldwide, consistently offering some of the lowest spot GPU rental prices available anywhere. Both on-demand and bid-based spot pricing are available, enabling researchers and developers to run LLM fine-tuning, image generation, and batch AI workloads at a fraction of traditional cloud costs. The largest and most price-competitive GPU marketplace for budget-conscious AI teams.
- Lowest spot prices
- Wide GPU variety
- Bid-based pricing
- Large host network
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.
Vast.ai — marketplace provider
Vast.ai is a peer-to-peer GPU marketplace listing 10,000+ GPUs — including H100, A100, and RTX 4090 — from hosts worldwide, consistently offering some of the lowest spot GPU rental prices available anywhere. Both on-demand and bid-based spot pricing are available, enabling researchers and developers to run LLM fine-tuning, image generation, and batch AI workloads at a fraction of traditional cloud costs. The largest and most price-competitive GPU marketplace for budget-conscious AI teams.
Billing model comparison
TensorDock uses a On-demand, Spot billing model with a minimum commitment of None. Vast.ai uses On-demand, Spot (bid-based) 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. Vast.ai is best suited for: Budget-conscious developers, Spot-tolerant batch jobs, Researchers needing cheap GPUs. Its key strengths are lowest spot prices, wide gpu variety, bid-based pricing. Marketplace providers aggregate GPU supply from multiple sources, often offering the lowest spot rates but with more variable availability and less predictable performance compared to dedicated providers.
Support tiers and region coverage
TensorDock offers Community → Pro support across 4 regions (US, EU, APAC and 1 more). Vast.ai offers Community → Pro support across 4 regions (US, EU, APAC and 1 more). Both providers have comparable region coverage — choose based on which specific regions overlap with your user base or data residency requirements.
Provider background: TensorDock vs Vast.ai
TensorDock was founded in 2020 and is headquartered in Boston, MA. Vast.ai was founded in 2017 and is headquartered in San Francisco, CA. Vast.ai has 3 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.