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
iRender is a GPU cloud provider specializing in AI training, 3D rendering, and VFX workloads, offering RTX 4090, A100, and H100 instances with competitive APAC pricing across global nodes. On-demand hourly GPU rental makes it accessible for creative studios and AI teams in Southeast Asia and beyond who need high-performance GPU compute for both rendering pipelines and model training. A strong choice for APAC-based teams that need a single platform for both AI and creative GPU workloads.
- Competitive APAC pricing
- RTX 4090 availability
- Rendering-optimized
- Global nodes
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.
iRender — specialist provider
iRender is a GPU cloud provider specializing in AI training, 3D rendering, and VFX workloads, offering RTX 4090, A100, and H100 instances with competitive APAC pricing across global nodes. On-demand hourly GPU rental makes it accessible for creative studios and AI teams in Southeast Asia and beyond who need high-performance GPU compute for both rendering pipelines and model training. A strong choice for APAC-based teams that need a single platform for both AI and creative GPU workloads.
Billing model comparison
AWS uses a On-demand, Reserved (1yr/3yr), Spot billing model with a minimum commitment of None (on-demand). iRender uses On-demand (hourly) billing with a None minimum. AWS's no-commitment on-demand model is more flexible for short-term or experimental workloads, while iRender'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. iRender is best suited for: 3D rendering, AI training, APAC-based teams, Creative workloads. Its key strengths are competitive apac pricing, rtx 4090 availability, rendering-optimized. As a hyperscaler, AWS offers broader ecosystem integration and compliance certifications at a premium price. iRender 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). iRender offers Community → Standard support across 3 regions (APAC, US, EU). 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 iRender
AWS was founded in 2006 and is headquartered in Seattle, WA. iRender was founded in 2019 and is headquartered in Hanoi, Vietnam. AWS has 13 years more operational history than iRender, 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.