Supported GPU Hardware
Access the latest NVIDIA GPUs for your workloads. From development to large-scale training.
RTX A5000
RTX 3090
RTX A6000
RTX 4090
A40
L4
L40
L40S
A100 PCIe
H100 PCIe
Everything included
Each pod comes with the capabilities you need for productive ML work.
GPU/CPU Provisioning
Provision pods with the GPU or CPU resources you need. Scale up or down based on your workload requirements.
Persistent Workspace Storage
Each pod includes attached workspace disk. Data persists across restarts for notebooks, experiments, and artifacts.
Prebuilt ML Environments
Launch with Jupyter, PyTorch, TensorFlow pre-installed. Skip environment setup and start working immediately.
Isolated Environments
Pods are isolated per user or project. Your data and processes are separate from other users.
Resource Metrics
Monitor CPU, GPU, memory, and disk usage in real-time. Understand resource consumption for your workloads.
Pod Logs
Access logs for debugging and monitoring. Track what's happening inside your pod environment.
Built for ML workflows
GPU Pods are ideal for interactive and long-running ML workloads.
Development & Experimentation
Spin up GPU-enabled notebooks for rapid prototyping. Test ideas, explore datasets, and iterate quickly.
Long-running Training Jobs
Run model training that takes hours or days. Persistent storage keeps your data safe across restarts.
Interactive Research
Notebook-based workflows for ML research. Access powerful GPUs with familiar tools like Jupyter.
Custom Environments
Need something specific? Custom images can be supported. Run the exact environment your project requires.