GPU Per Hour
Real-time cloud GPU price comparison: Find the cheapest H100, A100, RTX 4090 & more across 30+ providers. Deploy instantly and save big on hourly rentals.
A startup from Austin, the United States.
Real-time cloud GPU price comparison: Find the cheapest H100, A100, RTX 4090 & more across 30+ providers. Deploy instantly and save big on hourly rentals.
A startup from Austin, the United States.
This page is designed to help you find out whether GPU Per Hour is good and if it is the right choice for you.
GPU Per Hour tracks real-time pricing across 30+ GPU cloud providers so you don't overpay for compute.
The same GPU can cost 63x more depending on where you rent it. A Tesla V100 ranges from $0.05/hr to $3.06/hr. An H100 ranges from $0.80/hr to $5.95/hr. We surface these differences so you can make informed decisions.
Features: - Real-time price updates across 30+ providers - Filter by GPU type, VRAM, price - See actual availability, not just listed inventory - Compare providers like RunPod, Vast.ai, Lambda Labs, CoreWeave, TensorDock, and more
Built for ML engineers, researchers, and indie hackers who don't want to pay AWS prices for commodity hardware.
Listed in
Cost-Effective GPU Access
Provides on-demand GPU rental at potentially lower costs compared to purchasing and maintaining physical hardware, making it attractive for users with intermittent or short-term computing needs.
Flexible Pay-As-You-Go Model
Users can pay only for the hours they actually use the GPU resources, avoiding large upfront capital investments in expensive hardware.
Scalability
Allows users to scale their computing resources up or down based on project demands, which is useful for machine learning, rendering, or other GPU-intensive tasks that have variable workloads.
No Maintenance Overhead
Eliminates the need for users to handle hardware maintenance, cooling, power management, and upgrades since the infrastructure is managed by the service provider.
Accessibility for Small Teams and Individuals
Makes high-performance GPU computing accessible to individual developers, researchers, and small businesses who may not have the budget for enterprise-level hardware.
GPU Per Hour appears to be a GPU rental marketplace/service offering on-demand access to computing power, which can be a good option for users needing flexible, pay-as-you-go GPU resources without long-term commitments, though thorough due diligence on pricing, reliability, and support is recommended before committing significant workloads.
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