Describe the workload
Training, inference, experimentation, and data preparation have different requirements. Record expected model sizes, concurrency, runtime needs, and the way the team will share resources.
Look beyond compute
GPU memory is one constraint. Storage throughput, CPU, system memory, network bandwidth, power, cooling, and physical space can also shape the design.
Compare operating models
Evaluate cloud, local, and private infrastructure against utilization, data handling, flexibility, and operating responsibility. Avoid choosing solely on a hardware specification or headline hourly price.
Validate with a pilot
Run a representative workload, observe resource use, and document the environment. Use measured behavior to guide capacity decisions before expanding.