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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.