Provider Overview
Strengths & Best For
RunPod is a community GPU cloud marketplace offering H100, A100, RTX 4090, and RTX 3090 instances on both on-demand and spot GPU rental plans, consistently among the lowest-cost options available. Its spot instances make it especially popular with indie AI developers running batch inference, image generation, and LLM fine-tuning on a budget. A serverless GPU option is also available for per-second billing on inference endpoints.
- Very competitive pricing
- Wide GPU selection
- Spot instances
- Serverless GPU option
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
RunPod — specialist provider
RunPod is a community GPU cloud marketplace offering H100, A100, RTX 4090, and RTX 3090 instances on both on-demand and spot GPU rental plans, consistently among the lowest-cost options available. Its spot instances make it especially popular with indie AI developers running batch inference, image generation, and LLM fine-tuning on a budget. A serverless GPU option is also available for per-second billing on inference endpoints.
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
RunPod uses a On-demand, Spot (interruptible) 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
RunPod is best suited for: Budget-conscious developers, Experimentation, Batch inference jobs. Its key strengths are very competitive pricing, wide gpu selection, spot instances. 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
RunPod offers Community → Pro support across 3 regions (US, EU, CA). GPUhub offers Standard support across 2 regions (VN, APAC). RunPod's broader region footprint gives it an advantage for latency-sensitive workloads or teams with data residency requirements in specific geographies.
Provider background: RunPod vs GPUhub
RunPod was founded in 2022 and is headquartered in San Francisco, CA. GPUhub was founded in 2021 and is headquartered in Ho Chi Minh City, Vietnam. GPUhub has 1 years more operational history than RunPod, 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.