Use Cases
Bare Metal GPU Servers are designed for users who need full hardware access and control to maximize AI/ML performance. It supports highly parallelized workloads with multiple GPUs, dedicated networking, and deep customization for training pipelines and inference systems.
Bare Metal GPU Servers provide the following:
- A way to consume powerful, pre-configured physical machines that are optimized for advanced AI/ML workloads.
- Full access to GPUs, CPUs, memory, storage, and networking resources with zero virtualization overhead.
Bare Metal GPU Servers are optimized for:
- Large Language Model (LLM) training and fine-tuning
- Multi-GPU distributed training jobs
- High-throughput inference pipelines
- Data preprocessing and feature engineering
- Serving orchestration or control plane components
By Server Type¶
End users can select the Bare Metal configuration best suited for their compute needs.
8-GPU Node (8× H100 SXM5)¶
Ideal for high-end distributed training, LLM finetuning, and dense AI model workloads.
4-GPU Node (4× L40S)¶
Balanced option for training, inferencing, and high-throughput tasks.
CPU Node (No GPU)¶
Recommended for orchestration layers, storage controllers, and prep workloads.