Local GPU or cloud GPU for an existing workstation?

If you already own a suitable GPU, compare the additional cost of using it with the cloud bill. The purchase price is a separate decision from whether to run today’s job locally.

Check whether the local machine meets the workload

Start with GPU memory, software support and host resources. Use the model memory estimates for a model-based workload, then account for its stated limitations. A cloud GPU with more memory can be useful even when the local machine’s electricity cost is lower.

An interactive application can also depend on storage access, an operating-system licence or a remote desktop. A compute-only rental price does not establish that those are included.

Compare the incremental bill

For the local GPU electricity estimate, multiply watts divided by 1,000 by your electricity price per kWh and by runtime. Enter your own power estimate; the GPU’s specification limit is not a measured workload draw. Include other system costs separately if they affect the decision.

For cloud use, multiply the total node rate by billed runtime, then add applicable storage and transfer. The job calculator makes those components explicit.

Keep a future purchase separate

If the existing GPU does not meet the workload and you are considering new hardware, use the rent-versus-buy calculator. It includes purchase price and an electricity estimate, but it does not value resale, setup time, cooling or the option to switch to different hardware later.