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
Lyceum is an academic GPU cloud offering H100 and A100 instances with research-friendly policies, flexible on-demand pricing, and configurations tailored for AI experimentation and academic research teams. Accessible pricing and a focus on the research community make it a practical option for universities and independent researchers who need GPU compute for LLM experimentation and model training without enterprise overhead. A strong choice for academic AI teams that want affordable, flexible GPU access.
- Research-friendly
- Flexible pricing
- Academic focus
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.
Lyceum — specialist provider
Lyceum is an academic GPU cloud offering H100 and A100 instances with research-friendly policies, flexible on-demand pricing, and configurations tailored for AI experimentation and academic research teams. Accessible pricing and a focus on the research community make it a practical option for universities and independent researchers who need GPU compute for LLM experimentation and model training without enterprise overhead. A strong choice for academic AI teams that want affordable, flexible GPU access.
Billing model comparison
AWS uses a On-demand, Reserved (1yr/3yr), Spot billing model with a minimum commitment of None (on-demand). Lyceum uses On-demand billing with a None minimum. AWS's no-commitment on-demand model is more flexible for short-term or experimental workloads, while Lyceum'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. Lyceum is best suited for: Academic research, AI experimentation, Small teams. Its key strengths are research-friendly, flexible pricing, academic focus. As a hyperscaler, AWS offers broader ecosystem integration and compliance certifications at a premium price. Lyceum 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). Lyceum offers Standard 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 Lyceum
AWS was founded in 2006 and is headquartered in Seattle, WA. Lyceum was founded in 2023 and is headquartered in United States. AWS has 17 years more operational history than Lyceum, 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.