Rent NVIDIA H100 PCIE GPU by the hour
The NVIDIA H100 PCIE is a Hopper-architecture datacenter GPU built for demanding deep learning and scientific computing workloads. It provides 80 GB of VRAM, about 1760 GB/s of memory bandwidth, and about 41.0 TFLOPS of standard floating-point compute within a 350 W power envelope. On Cloudj, you can deploy this compute capability 9.0 accelerator with per-hour billing and full SSH access.
Specifications
VRAM per GPU
80 GB
Architecture
NVIDIA Hopper
Compute capability
9
FP32 compute
≈ 41 TFLOPS
Memory bandwidth
≈ 1760 GB/s
Power limit
350 W
Values reported by the infrastructure provider for machines currently listed; real performance varies by machine.
Available configurations
Live stock and prices, updated continuously. The final price is confirmed before you order.
Rent nowWhat the H100 PCIE is good for
Large Language Model Inference
Serve large language models in memory using the 80 GB of VRAM and high memory bandwidth alongside pre-configured vLLM or Ollama templates.
Model Fine-Tuning and Training
Train or fine-tune deep neural networks using the Hopper architecture and ready PyTorch/CUDA environments.
Batch Image Generation
Run high-throughput diffusion pipelines and complex ComfyUI workflows that benefit from substantial memory capacity.
Data Science and Simulation
Execute compute-intensive simulations and data processing tasks with about 41.0 TFLOPS of standard floating-point performance and about 1760 GB/s of memory throughput.
Is it the right GPU for you?
Choose the H100 PCIE when your workloads require 80 GB of VRAM, datacenter-grade memory bandwidth, and Hopper compute capability 9.0 features. For lighter inference or smaller models, a workstation or consumer GPU with less VRAM is more economical, while extreme throughput requirements may warrant an SXM-based datacenter variant.
Frequently asked questions
Rent the H100 PCIE by the hour
Create an account, choose a configuration and connect over SSH. Billing stops when you delete the GPU.