NVIDIA GPUs Cloud Pricing
NVIDIA dominates the cloud GPU market with architectures spanning from Ampere to Blackwell. Their CUDA ecosystem and Tensor Cores make them the default choice for machine learning training, inference, and high-performance computing. Most cloud providers carry NVIDIA hardware across all performance tiers.
NVIDIA GPUs Available in the Cloud
A10
A100 PCIE
A100 PCIe 80GB
ServerA100 SXM
A100 SXM 40GB
ServerA16
ServerA2
ServerA30
ServerA40
B100
ServerB200
GB200
ServerGB300
ServerGH200
GTX 1050 Ti
GTX 1060
GTX 1070
GTX 1070 Ti
GTX 1080
GTX 1080 Ti
GTX 1650
GTX 1660
GTX 1660 SUPER
GTX 1660 Ti
GTX Titan X
H100 NVL
ServerH100 PCIe
ServerH100 SXM
ServerH200
HGX B300
ServerL4
ServerL40
L40S
Quadro P4000
Quadro P5000
Quadro RTX 4000
Quadro RTX 5000
Quadro RTX 6000
Quadro RTX 8000
RTX 2060
RTX 2060 SUPER
RTX 2070
RTX 2080
RTX 2080 Ti
RTX 3050
RTX 3060
RTX 3060 Ti
RTX 3070
RTX 3070 Ti
RTX 3080
RTX 3080 Ti
RTX 3090
RTX 3090 Ti
RTX 4000 Ada
RTX 4060
RTX 4060 Ti
RTX 4070
RTX 4070 SUPER
RTX 4070 Ti
RTX 4070 Ti SUPER
RTX 4080
RTX 4080 SUPER
RTX 4090
RTX 4500 Ada
RTX 5000 Ada
RTX 5060
RTX 5060 Ti
RTX 5070
RTX 5070 Ti
RTX 5080
RTX 5090
RTX 6000 Ada
RTX A2000
RTX A4000
RTX A4500
ServerRTX A5000
RTX A6000
RTX PRO 4000
RTX PRO 4500
RTX PRO 5000
RTX PRO 6000
ServerTesla P40
ServerTesla T4
Tesla V100
Titan RTX
Titan Xp
Sample NVIDIA GPUs Pricing
| Provider | Price / hr |
|---|---|
$0.410/hr 1× | |
$0.440/hr 1× | |
$0.551/hr 2× | |
$0.890/hr 1× | |
$1.49/hr 1× | |
$1.89/hr 1× | |
$2.09/hr 7× | |
$3.22/hr 1× | |
$18.00/hr 1× |
Showing 9 of 1838 price points. Visit individual GPU pages above for full pricing.
Frequently Asked Questions
Which NVIDIA GPU is best for ML training?
For large-scale training, the H100 and B200 offer the highest throughput with HBM3/HBM3e memory and NVLink interconnects. For smaller workloads and fine-tuning, the A100 80GB and RTX 4090 provide strong performance at lower cost. Check current pricing above to compare.
What is the difference between consumer and server NVIDIA GPUs?
Server GPUs (A100, H100, B200) use ECC memory, support NVLink/NVSwitch for multi-GPU scaling, and have higher memory capacities (40–192 GB HBM). Consumer GPUs (RTX 4090, RTX 3090) use GDDR6X with lower VRAM but can still be cost-effective for inference and smaller training jobs.