Nova Cloud vs Yotta: GPU Compute Price Comparison
Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for Nova Cloud and Yotta. Updated July 2026.
Provider Overview
Strengths & Best For
Nova Cloud is a Canadian self-serve GPU rental platform with in-house datacenter infrastructure offering RTX 5090 and RTX PRO 6000 instances — some of the newest consumer and professional GPU hardware available in any cloud. On-demand billing with a $15 signup credit makes it easy to get started with AI training, inference, or rendering workloads without a long-term commitment. A strong option for Canadian teams and developers wanting the latest NVIDIA GPU hardware at competitive prices.
- RTX 5090 availability
- In-house datacenter
- $15 signup credit
- Canadian infrastructure
Yotta Infrastructure is an Indian hyperscale data center and cloud provider offering H100 and A100 GPU instances with Indian data residency and enterprise-grade infrastructure for AI training and HPC workloads. On-demand and reserved billing options are available, making it one of the most capable domestic GPU cloud options for Indian enterprises with data sovereignty requirements. A strong choice for APAC-based organizations needing high-performance GPU compute within India.
- Indian data residency
- Hyperscale infrastructure
- H100 availability
- Enterprise SLAs
Live GPU Pricing
Region Coverage
Popular Comparisons
Nova Cloud — specialist provider
Nova Cloud is a Canadian self-serve GPU rental platform with in-house datacenter infrastructure offering RTX 5090 and RTX PRO 6000 instances — some of the newest consumer and professional GPU hardware available in any cloud. On-demand billing with a $15 signup credit makes it easy to get started with AI training, inference, or rendering workloads without a long-term commitment. A strong option for Canadian teams and developers wanting the latest NVIDIA GPU hardware at competitive prices.
Yotta — specialist provider
Yotta Infrastructure is an Indian hyperscale data center and cloud provider offering H100 and A100 GPU instances with Indian data residency and enterprise-grade infrastructure for AI training and HPC workloads. On-demand and reserved billing options are available, making it one of the most capable domestic GPU cloud options for Indian enterprises with data sovereignty requirements. A strong choice for APAC-based organizations needing high-performance GPU compute within India.
Billing model comparison
Nova Cloud uses a On-demand billing model with a minimum commitment of None. Yotta uses On-demand, Reserved 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
Nova Cloud is best suited for: Canadian teams, RTX 5090 workloads, Budget-conscious developers. Its key strengths are rtx 5090 availability, in-house datacenter, $15 signup credit. Yotta is best suited for: India-based AI teams, APAC enterprise workloads, Regional data residency. Its key strengths are indian data residency, hyperscale infrastructure, h100 availability. 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
Nova Cloud offers Community → Standard support across 1 region (CA-Central). Yotta offers Standard → Enterprise support across 2 regions (IN-West, IN-South). Yotta's broader region footprint gives it an advantage for latency-sensitive workloads or teams with data residency requirements in specific geographies.
Provider background: Nova Cloud vs Yotta
Nova Cloud was founded in 2018 and is headquartered in Toronto, Canada. Yotta was founded in 2019 and is headquartered in Mumbai, India. Nova Cloud has 1 years more operational history than Yotta, 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.