Below is a price snapshot for single A100 80GB GPU rental rates (as of June 2026). All numbers are on-demand, pay-by-the-hour in a U.S. region unless noted.
| Provider | Instance | On-Demand $/GPU-hr* | Notes |
|---|---|---|---|
| Thunder Compute | $0.78 | On-demand | |
| TensorDock | $0.93 | Marketplace-style pricing from public listings | |
| Hyperstack | $1.35 | Public listed single-GPU equivalent | |
| Sesterce | $1.36 | Public listed single-GPU equivalent | |
| Runpod Community Cloud | $1.39 | Community marketplace rate; varies by supply | |
| JarvisLabs | $1.49 | Pay-as-you-go A100 instance pricing | |
| Crusoe Cloud | $1.65 | Public listed hourly pricing | |
| Verda | $1.79 | Public listed single-GPU equivalent | |
| Vast.ai | $1.94 | Average marketplace pricing. | |
| Lambda | $2.79 | Flat per-GPU rate | |
| Paperspace | $3.18 | Public listed price | |
| AWS EC2 | p4de.24xlarge | $3.43 | $27.44/hr VM ÷ 8 GPUs |
| Azure | ND24ads A100 v4 | $3.67 | Public listed single-GPU VM |
| Google Cloud | a2-ultragpu-1g | $5.07 | |
| FluidStack | Custom Quote | No public single-GPU on-demand rate | |
| Single-GPU costs are shown for multi-GPU nodes for easy comparison. Network, storage, and egress fees are not included. | |||
Thunder Compute is about 6.5x cheaper than GCP for a single A100 and still 1.5-4.4x cheaper than AWS, Lambda, Paperspace, and Azure.
Methodology
(Why you can trust these numbers)
- On-demand only: No reserved-instance, commitment, or prepaid discounts.
- Same class of silicon: All providers offer NVIDIA A100 80 GB GPUs.
- Public price lists: Each figure comes from the vendor's current pricing page on the date above.
- USD in U.S. regions: Rates in other regions can differ by 5-20%.
- We update this data every month.
Why this Matters for Developers
This chart compares how much it costs to run an NVIDIA A100 for 10 hours across major cloud providers.
Even small differences in hourly pricing add up quickly. A workload that costs $0.15 more per hour can translate into significantly higher monthly spend, especially for training jobs, batch processing, or production inference at scale.
See how different platforms stack up against each other in our breakdown of the cheapest cloud GPU providers.