Running in ~30 s
Pre-cached image, ports mapped, TLS terminated — the stack is working before you finish reading this.
Template · Base & frameworks · CUDA 13
Run CUDA on a cloud GPU, in 30 seconds
The bare CUDA base image — drivers, toolkit, SSH and Jupyter. Build your own stack on top. The bare CUDA image is the blank canvas: the NVIDIA driver stack, the CUDA 13 toolkit, nvcc, cuDNN, SSH and JupyterLab — nothing else. Use it to compile custom kernels, build your own framework stack, or reproduce a paper environment exactly, without fighting a pre-baked image. From $0.131/hr on an interruptible RTX 4090.
Template is free
You pay the GPU price only: NVIDIA CUDA on a RTX 4090 is $0.262/hr on-demand, $0.131/hr interruptible, billed per second.
Volumes for state
Models, datasets and outputs live on a $0.08/GB/mo volume; the instance stays disposable.
Private by default
Dedicated GPU, encrypted disk, crypto payments, no KYC, no stored IPs — Jupyter and SSH behind your own credentials.
Best GPUs for NVIDIA CUDA
Three price points that run this template well — Good, Better, Best. Every model in the catalogue works; these are the value picks.
| Tier | GPU | VRAM | On-demand | Interruptible | Why this card | Action |
|---|---|---|---|---|---|---|
| Good | RTX 4090 | 24 GB | $0.262 | $0.131 | Cheap Ada card for compiling and testing kernels interactively. | Deploy |
| Better | A100 SXM4 | 80 GB | $0.583 | $0.291 | Datacenter Ampere with FP64 and MIG for library development. | Deploy |
| Best | H100 SXM | 80 GB | $1.587 | $0.793 | Hopper features (FP8, TMA, thread-block clusters) for kernels that target the latest architecture. | Deploy |
Need more VRAM? The full catalogue lists all 76 models with live availability; the VRAM guide sizes models to cards.
Deploy NVIDIA CUDA from the console, CLI or API
Pick the template in the console deploy bar, or script it:
- Console — filter by GPU, choose NVIDIA CUDA in the template picker, set disk and env, deploy.
- CLI — pip install powergpu, then the command on the right. CLI reference.
- API — POST /v1/instances with "template": "nvidia-cuda". REST reference.
- Own image — any OCI reference works too; we inject the NVIDIA runtime. Template docs.
$ powergpu launch --gpu rtx-4090 --template nvidia-cuda \
--disk 100 --volume models:/workspace/models
✓ instance i-7a41c0e2 running (27.9s)
# NVIDIA CUDA · RTX 4090 · $0.262/hr · per second
# https://i-7a41c0e2.powergpu.io:8888 (TLS)
$ powergpu stop i-7a41c0e2 # billing ends this secondWhat is inside the NVIDIA CUDA template
| Image | powergpu/base:cuda13 |
|---|---|
| CUDA | CUDA 13 |
| Access | also builds for ARM hosts · SSH shell · JupyterLab on a mapped port |
| Category | Base & frameworks |
| Storage | Instance NVMe disk (sized at deploy) + optional network volumes |
| Billing | GPU price only, per second — no template fee, no setup fee |
Other base & frameworks templates
PyTorch on a cloud GPU — The training and research default: PyTorch 2.6, cuDNN, JupyterLab and SSH out of the box.
TensorFlow CUDA on a cloud GPU — TensorFlow with GPU support, Keras and TensorBoard on a mapped port.
PyTorch NGC on a cloud GPU — NVIDIA's NGC-optimised PyTorch build — tuned kernels for the datacenter cards.- NVIDIA RAPIDS on a cloud GPU — GPU-accelerated data science — cuDF, cuML, cuGraph in a notebook.
All-in-One App Studio on a cloud GPU — A launcher bundling the most-used AI apps behind one desktop — pick and run.- All 37 templates
NVIDIA CUDA on a cloud GPU: FAQ
Environment variables, ports and custom images are covered in the template docs.
How much does it cost to run NVIDIA CUDA on a cloud GPU?
Only the GPU price — the template is free. From $0.131/hr on an interruptible RTX 4090, $0.262/hr on-demand on a RTX 4090. Billing is per second, so an hour of tinkering costs an hour, not a day. Storage is $0.08/GB/month.
How long does NVIDIA CUDA take to start?
About 30 seconds from the deploy click: the image is pre-cached on hosts, ports are mapped and TLS is terminated for you. Restarting a stopped instance is faster, and your disk is exactly as you left it.
Can I keep my models and outputs between sessions?
Yes — attach a volume at deploy. Everything on the volume survives instance destruction and mounts on the next instance in the region in seconds, at $0.08/GB/month. The instance disk itself survives stop/start but not destroy.
Which CUDA version does the template ship?
CUDA 13 userspace on hosts running the current NVIDIA production driver. Templates pinned to CUDA 12.x exist for frameworks that need them; the offer card shows the maximum CUDA each machine supports.