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 SXM
A16
ServerA2
ServerA30
ServerA40
B100
ServerB200
GB200
ServerGB300
ServerGH200
H100 NVL
ServerH100 PCIe
ServerH100 SXM
ServerH200
HGX B300
ServerL4
ServerL40
L40S
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
RTX 5060
RTX 5060 Ti
RTX 5070
RTX 5070 Ti
RTX 5080
RTX 5090
RTX 6000 Ada
RTX 6000 Pro
RTX A2000
RTX A4000
RTX A4500
ServerRTX A5000
RTX A6000
RTX PRO 6000
ServerTesla T4
Tesla V100
Sample NVIDIA GPUs Pricing
Showing 9 of 719 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.