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Before the long reservation: a GPU server acceptance checklist

An SSH login proves access. It does not prove the configuration, application readiness or recovery path you agreed to buy.

· Arvica Cloud · Analysis & buying guide

Write the acceptance record before delivery

Prepare a short record with the quoted GPU variant and count, dedicated or shared allocation, VM or bare-metal delivery, CPU and RAM, storage persistence, region and term. Add an owner for each unresolved item and an agreed deadline. Distinguish requirements that block acceptance from preferences. This prevents an avoidable dispute in which the seller delivered a server while the buyer expected a ready-to-run application environment.

Verify identity and visible hardware

On your assigned host, nvidia-smi provides GPU and driver information; its topology functions can help inspect visible device relationships. [1] Save a dated, redacted record and compare it with the order. Confirm storage mounts and usable capacity separately. These checks establish what the environment exposes, not infrastructure ownership or an independent guarantee of physical isolation. If a tenancy guarantee matters, obtain it in the service agreement.

Run your smallest meaningful workload

Use the intended container or environment version and a representative non-sensitive input. Check model loading, one complete inference or training segment, output validity and a save-and-reload cycle. Then run a bounded concurrency or batch trial with an agreed charge ceiling. Do not publish credentials or customer data in the evidence bundle. A synthetic stress test can supplement this exercise, but it should not replace application acceptance.

Close the operational and billing loop

Document how to contact support, which failures require a replacement, how persistent data is recovered and how service termination is requested. Clarify when billing begins, what continues to accrue after stopping compute and the agreed treatment of a failed acceptance test. These are questions to settle in the actual order, not promises of universal service terms. Send Arvica the completed requirements so the proposed configuration and delivery conditions can be reviewed together.

Sources

Reviewed: 2026-09-11

  1. NVIDIA — System Management Interface

Apply this to your workload

Further reading

How much GPU memory does a 70B model really need?

Your GPU is busy waiting: investigate the pipeline before renting more

Eight GPUs are not automatically eight times faster

AI inference economics: why the GPU-hour is only the starting point

B300 and Rubin: plan the workload before chasing the roadmap

AI data-centre power demand: what compute buyers should ask

Reserved vs on-demand GPUs: calculate the utilisation break-even