Deployments
Choose a machine image
Choose an image compatible with your GPU vendor and workload from the current catalog.
3 min read · UpdatedStart with the workload
Choose a general-purpose image if you intend to install your own stack, or a framework image for a specific workflow. The table below is generated from the same catalog as the deployment selector.
The available image list changes with the GPU vendor. Switching to an incompatible vendor resets the selection to a compatible image. The server also validates compatibility, including requests made directly through the API.
Images in the catalog
These labels describe the configured image templates. The local demo does not boot containers or validate the installed packages of a remote machine.
| Image | Catalog label | GPU vendors |
|---|---|---|
Ubuntu 24.04ubuntu | CUDA ready | NVIDIA, AMD |
PyTorch 2.8pytorch | CUDA 12.8 | NVIDIA |
vLLMvllm | OpenAI-compatible API | NVIDIA, AMD |
ComfyUIcomfyui | Flux & SDXL | NVIDIA |
Ollamaollama | Local model server | NVIDIA, AMD |
JAXjax | CUDA 12 | NVIDIA |
ROCm 6.4rocm | AMD optimized | AMD |
Debian 13debian | Minimal | NVIDIA, AMD |
Keep workloads reproducible
For a real workload, record the driver, runtime, framework version and model dependencies in your project. A template name alone is not a reproducible environment. Keep your training data and outputs backed up outside the rented node.