iRender vs Atlas Cloud: GPU Compute Price Comparison
Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for iRender and Atlas Cloud. Updated July 2026.
Provider Overview
Strengths & Best For
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
Atlas Cloud is an Iceland-based GPU cloud offering H100 and A100 instances powered by 100% renewable geothermal energy, combining high-performance AI compute with a genuinely carbon-neutral infrastructure footprint. Competitive on-demand pricing and low-latency connectivity to Europe make it an attractive sustainable GPU cloud for EU-based AI training and inference workloads. A top choice for sustainability-focused teams that want green GPU compute without sacrificing performance.
- 100% renewable energy
- Competitive H100 pricing
- Low latency to Europe
Live GPU Pricing
Region Coverage
Popular Comparisons
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.
Atlas Cloud — specialist provider
Atlas Cloud is an Iceland-based GPU cloud offering H100 and A100 instances powered by 100% renewable geothermal energy, combining high-performance AI compute with a genuinely carbon-neutral infrastructure footprint. Competitive on-demand pricing and low-latency connectivity to Europe make it an attractive sustainable GPU cloud for EU-based AI training and inference workloads. A top choice for sustainability-focused teams that want green GPU compute without sacrificing performance.
Billing model comparison
iRender uses a On-demand (hourly) billing model with a minimum commitment of None. Atlas Cloud uses On-demand billing with a None minimum. Both providers offer flexible billing options — compare the live pricing table above to find the best rate for your specific GPU model and workload duration.
Which workloads each provider suits best
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. Atlas Cloud is best suited for: Sustainability-focused teams, European AI workloads, Training runs. Its key strengths are 100% renewable energy, competitive h100 pricing, low latency to europe. 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
iRender offers Community → Standard support across 3 regions (APAC, US, EU). Atlas Cloud offers Standard support across 1 region (IS). iRender's broader region footprint gives it an advantage for latency-sensitive workloads or teams with data residency requirements in specific geographies.
Provider background: iRender vs Atlas Cloud
iRender was founded in 2019 and is headquartered in Hanoi, Vietnam. Atlas Cloud was founded in 2022 and is headquartered in Reykjavik, Iceland. iRender has 3 years more operational history than Atlas Cloud, 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.