Rent an NVIDIA H100 SXM GPU with 80 GB VRAM
Rent H100 SXM cloud GPU servers by the hour on Cloudj: 80 GB VRAM, NVIDIA Hopper, about 53.5 TFLOPS FP32 and 2869 GB/s of memory bandwidth. With a 700 W power limit, this is the H100 for teams that train, fine-tune and serve large models and want the fastest Hopper module in the lineup for compute. Pick a live configuration, start from the Ubuntu 22.04 + CUDA or PyTorch + JupyterLab template and connect over SSH with your key.
H100 SXM specifications
VRAM per GPU
80 GB
Architecture
NVIDIA Hopper
Compute capability
9
FP32 compute
≈ 53.5 TFLOPS
Memory bandwidth
≈ 2869 GB/s
Power limit
700 W
Values reported by the infrastructure provider for machines currently listed; real performance varies by machine.
Live H100 SXM configurations and prices
Out of stock right now
Browse available GPUsWhat you can run on the H100 SXM cloud GPU
Compute-heavy training
53.5 TFLOPS FP32 and a 700 W power limit give the H100 SXM the most compute of any Hopper card listed here.
Fast LLM inference
2869 GB/s of bandwidth speeds up token generation for 13B–34B models in 16-bit or quantized 70B models.
Full fine-tuning of 7B–13B models
80 GB leaves room for full-parameter fine-tuning of smaller LLMs, not just adapters, with the right optimizer settings.
Diffusion and video model training
Train or fine-tune image and video models where both memory and compute decide how long a run takes.
Is the H100 SXM the right GPU for your workload?
Choose the H100 SXM when your training or inference workloads require 80 GB of high-bandwidth datacenter memory and Hopper architecture features. A smaller workstation or consumer GPU is a more practical choice for lightweight development or small models, while a newer or higher-capacity datacenter GPU is preferable if a single instance cannot hold your entire model in 80 GB of VRAM.
Guides for H100 SXM
H100 SXM cloud GPU: frequently asked questions
Rent the H100 SXM cloud GPU by the hour
Pick a live configuration, choose a template and connect over SSH with your key. Billing stops when you destroy the instance.