AWS vs Latitude.sh: GPU Compute Price Comparison
Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for AWS and Latitude.sh. Updated July 2026.
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
Latitude.sh provides bare-metal H100, A100, and RTX 4090 servers with no virtualization overhead across US, EU, and Brazil data centers, delivering dedicated hardware performance for latency-sensitive AI inference and distributed training. On-demand and reserved billing options are available with predictable pricing and no noisy-neighbor effects. A top choice for teams that need bare-metal GPU performance with global reach including LATAM coverage.
- Bare-metal performance
- No virtualization overhead
- Brazil region
- Predictable pricing
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.
Latitude.sh — bare-metal provider
Latitude.sh provides bare-metal H100, A100, and RTX 4090 servers with no virtualization overhead across US, EU, and Brazil data centers, delivering dedicated hardware performance for latency-sensitive AI inference and distributed training. On-demand and reserved billing options are available with predictable pricing and no noisy-neighbor effects. A top choice for teams that need bare-metal GPU performance with global reach including LATAM coverage.
Billing model comparison
AWS uses a On-demand, Reserved (1yr/3yr), Spot billing model with a minimum commitment of None (on-demand). Latitude.sh uses On-demand, Reserved billing with a None minimum. AWS's no-commitment on-demand model is more flexible for short-term or experimental workloads, while Latitude.sh'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. Latitude.sh is best suited for: Performance-critical workloads, Latency-sensitive inference, LATAM teams. Its key strengths are bare-metal performance, no virtualization overhead, brazil region. 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
AWS offers Basic → Enterprise support across 5 regions (us-east-1, us-west-2, eu-west-1 and 2 more). Latitude.sh offers Standard → Enterprise support across 3 regions (US-East, EU-West, BR-South). 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 Latitude.sh
AWS was founded in 2006 and is headquartered in Seattle, WA. Latitude.sh was founded in 2020 and is headquartered in São Paulo, Brazil. AWS has 14 years more operational history than Latitude.sh, 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.