Provider Overview
Strengths & Best For
AWS offers on-demand, reserved, and spot GPU instances across EC2 P4d (A100), P5 (H100), and G6 (L40S) families, spanning 30+ global regions with enterprise SLAs and deep ML tooling via SageMaker. H100 and A100 clusters are available with InfiniBand networking for distributed LLM training and large-scale AI inference. The broadest ecosystem of any GPU cloud provider, making it the default choice for enterprises already invested in the AWS stack.
- Widest global region coverage
- Deep ecosystem integrations
- Enterprise SLAs
- Reserved instance discounts
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
AWS — hyperscaler provider
AWS offers on-demand, reserved, and spot GPU instances across EC2 P4d (A100), P5 (H100), and G6 (L40S) families, spanning 30+ global regions with enterprise SLAs and deep ML tooling via SageMaker. H100 and A100 clusters are available with InfiniBand networking for distributed LLM training and large-scale AI inference. The broadest ecosystem of any GPU cloud provider, making it the default choice for enterprises already invested in the AWS stack.
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
AWS uses a On-demand, Reserved (1yr/3yr), Spot billing model with a minimum commitment of None (on-demand). Vast.ai uses On-demand, Spot (bid-based) billing with a None minimum. AWS's no-commitment on-demand model is more flexible for short-term or experimental workloads, while Vast.ai's commitment requirement suits teams with predictable long-running jobs.
Which workloads each provider suits best
AWS is best suited for: Enterprise workloads, Production ML inference, Teams already on AWS. Its key strengths are widest global region coverage, deep ecosystem integrations, enterprise slas. 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
AWS offers Basic → Enterprise support across 5 regions (us-east-1, us-west-2, eu-west-1 and 2 more). Vast.ai offers Community → Pro support across 4 regions (US, EU, APAC and 1 more). AWS's broader region footprint gives it an advantage for latency-sensitive workloads or teams with data residency requirements in specific geographies.
Provider background: AWS vs Vast.ai
AWS was founded in 2006 and is headquartered in Seattle, WA. Vast.ai was founded in 2017 and is headquartered in San Francisco, CA. AWS has 11 years more operational history than Vast.ai, 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.