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
Brev.dev (part of NVIDIA) is a developer GPU cloud that provisions H100, A100, RTX 4090, L4, and T4 instances with one-command CLI provisioning and NVIDIA-optimized ML stacks pre-installed, eliminating environment setup for AI training and inference. On-demand per-second billing means you only pay for actual compute time, making it highly cost-efficient for iterative ML development and rapid prototyping. The fastest way to get an NVIDIA-optimized GPU environment running for LLM fine-tuning or model deployment.
- One-command provisioning
- NVIDIA-optimized environments
- Pre-built ML stacks
- Developer-friendly CLI
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.
Brev.dev — specialist provider
Brev.dev (part of NVIDIA) is a developer GPU cloud that provisions H100, A100, RTX 4090, L4, and T4 instances with one-command CLI provisioning and NVIDIA-optimized ML stacks pre-installed, eliminating environment setup for AI training and inference. On-demand per-second billing means you only pay for actual compute time, making it highly cost-efficient for iterative ML development and rapid prototyping. The fastest way to get an NVIDIA-optimized GPU environment running for LLM fine-tuning or model deployment.
Billing model comparison
AWS uses a On-demand, Reserved (1yr/3yr), Spot billing model with a minimum commitment of None (on-demand). Brev.dev uses On-demand (per-second) billing with a None minimum. AWS's no-commitment on-demand model is more flexible for short-term or experimental workloads, while Brev.dev'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. Brev.dev is best suited for: ML developers, Rapid prototyping, NVIDIA ecosystem users, Teams wanting zero setup. Its key strengths are one-command provisioning, nvidia-optimized environments, pre-built ml stacks. As a hyperscaler, AWS offers broader ecosystem integration and compliance certifications at a premium price. Brev.dev as a specialist provider typically offers lower per-GPU rates for teams that don't need the full hyperscaler ecosystem.
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). Brev.dev offers Community → Enterprise support across 1 region (US). 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 Brev.dev
AWS was founded in 2006 and is headquartered in Seattle, WA. Brev.dev was founded in 2021 and is headquartered in San Francisco, CA. AWS has 15 years more operational history than Brev.dev, 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.