CUDO Compute vs GPUhub: GPU Compute Price Comparison
Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for CUDO Compute and GPUhub. Updated July 2026.
Provider Overview
Strengths & Best For
CUDO Compute provides managed H100 and A100 GPU clusters powered by green energy, combining enterprise SLAs with a sustainability-first mission for large-scale AI training and LLM workloads. On-demand and reserved billing options are available across EU and US regions, with EU data residency for GDPR-compliant workloads. A strong choice for enterprises that need both high-performance GPU infrastructure and verifiable green compute credentials.
- Green energy focus
- Managed clusters
- Enterprise SLAs
- EU data residency
GPUhub is a Southeast Asian GPU cloud based in Vietnam, offering H100, A100, and RTX instances at affordable APAC pricing for AI and ML workloads across the region. On-demand billing and local support make it one of the most accessible GPU cloud options for Vietnamese and Southeast Asian teams running LLM training, fine-tuning, and inference workloads. A strong regional option for APAC-based developers who want low-latency GPU access at competitive local prices.
- APAC presence
- Affordable pricing
- Local support
Live GPU Pricing
Region Coverage
Popular Comparisons
CUDO Compute — specialist provider
CUDO Compute provides managed H100 and A100 GPU clusters powered by green energy, combining enterprise SLAs with a sustainability-first mission for large-scale AI training and LLM workloads. On-demand and reserved billing options are available across EU and US regions, with EU data residency for GDPR-compliant workloads. A strong choice for enterprises that need both high-performance GPU infrastructure and verifiable green compute credentials.
GPUhub — specialist provider
GPUhub is a Southeast Asian GPU cloud based in Vietnam, offering H100, A100, and RTX instances at affordable APAC pricing for AI and ML workloads across the region. On-demand billing and local support make it one of the most accessible GPU cloud options for Vietnamese and Southeast Asian teams running LLM training, fine-tuning, and inference workloads. A strong regional option for APAC-based developers who want low-latency GPU access at competitive local prices.
Billing model comparison
CUDO Compute uses a On-demand, Reserved billing model with a minimum commitment of None. GPUhub 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
CUDO Compute is best suited for: Sustainable AI workloads, Enterprise training, EU-based teams. Its key strengths are green energy focus, managed clusters, enterprise slas. GPUhub is best suited for: Southeast Asian teams, Cost-sensitive AI workloads, APAC inference. Its key strengths are apac presence, affordable pricing, local support. 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
CUDO Compute offers Standard → Enterprise support across 3 regions (EU-West, US-East, APAC). GPUhub offers Standard support across 2 regions (VN, APAC). CUDO Compute's broader region footprint gives it an advantage for latency-sensitive workloads or teams with data residency requirements in specific geographies.
Provider background: CUDO Compute vs GPUhub
CUDO Compute was founded in 2021 and is headquartered in London, UK. GPUhub was founded in 2021 and is headquartered in Ho Chi Minh City, Vietnam. Both providers were founded in the same year — evaluate them on current pricing, region coverage, and support tier rather than operational history. 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.