AI GPU Server
A rack server configured with accelerators for model training or inference, deployable inside the organisation rather than in a public cloud.
How to choose
Accelerator count, memory per accelerator and interconnect are set by the model size and concurrency the workload actually needs. Power and cooling capacity in the rack are usually the real constraint.
Typical applications
- Private LLM and RAG
- Computer vision inference
- On-premise AI for regulated data
Specifications
Exact specifications depend on the manufacturer and variant selected for your project. We confirm them against the supplier datasheet before quoting rather than publishing indicative figures here.
Enterprise AI server platforms
Choose a Supermicro-style GPU server architecture based on model size, concurrent users, storage, networking, power and cooling. Final hardware is confirmed through an engineering review.
