gpu.fm

Purpose-Built for AI Training

Our training pods are engineered for maximum throughput on large language models, computer vision, and multi-modal AI workloads. Each configuration is validated for thermal performance, power delivery, and network topology.

Choose from pre-configured pods or work with our team to design a custom cluster that matches your training requirements and budget.

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  8x GPU SERVER

Training Pod Configurations

4× H200 Training Node

Entry-level training pod for fine-tuning and research

GPUs:4× NVIDIA H200 (141GB)
Memory:564 GB HBM3e
Interconnect:NVLink 4th Gen
Power:~3.6 kW
Rack Space:4U
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8× H200 Training Pod

Production training for 70B+ parameter models

GPUs:8× NVIDIA H200 (141GB)
Memory:1.1 TB HBM3e
Interconnect:NVLink + InfiniBand
Power:~7.2 kW
Rack Space:8U
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8× MI300X Training Pod

Cost-effective alternative with massive memory

GPUs:8× AMD MI300X (192GB)
Memory:1.5 TB HBM3
Interconnect:Infinity Fabric + IB
Power:~6.0 kW
Rack Space:8U
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What's Included

Validated Topology

Pre-tested network and storage configurations optimized for distributed training frameworks (PyTorch, JAX, DeepSpeed).

Thermal Management

Liquid or air cooling solutions designed for sustained 100% GPU utilization with proper airflow and redundancy.

Power Distribution

Redundant PSUs and PDUs with proper circuit planning to handle peak power draw during training runs.

Installation Support

Optional white-glove installation, rack integration, and initial system validation at your facility.

Warranty & RMA

Manufacturer warranty with expedited RMA process. We handle all vendor coordination and logistics.

Flexible Fulfillment

Dropship from distributor or staged assembly and testing before delivery to your datacenter.

Need a Custom Training Cluster?

Our team can design a multi-node training cluster tailored to your model architecture, budget, and datacenter constraints.