Dual RTX 5090 AI Workstation

Choose dual GPUs when your team needs to run more than one workload simultaneously, fine-tune larger models, or sustain higher throughput than a single card allows. The clearest test is whether you have two jobs or one oversized job. Two jobs, such as a served model plus a training run, or two engineers experimenting, map cleanly onto two cards with no shared-memory overhead at all. One job too large for 32GB also justifies it. What does not justify it is hoping a model that already fits will run twice as fast; sharding across cards costs communication time, and the speed-up on a single fitted model is usually well short of double.

Under sustained dual-GPU load it is best placed in a server room or well-ventilated area. We configure the thermal and acoustic profile to your environment and advise accordingly. In practical terms, two cards under continuous load push the fans hard enough that most people find it distracting at a desk, and the machine returns close to everything it draws to the room as heat. If the only available location is an office, tell us, and we would rather change the cooling design, or point you at a rack server in a room that is already cooled, than deliver something you end up switching off.

On 230V mains a 2000W supply sits comfortably within a normal socket circuit. On 120V it should have a dedicated 20A circuit and nothing else of consequence on it, because a standard 15A circuit does not leave enough continuous headroom for a machine of this class plus anything else in the room. If you are fitting more than one of these in the same space, treat it as an electrical planning question and involve whoever manages the building, ideally before the order rather than on the delivery day.

This is a tower configuration. If you anticipate moving to rack infrastructure, we can advise on our GPU Server line as the appropriate next step. Converting a tower into a rack machine is rarely worth doing, because the chassis, airflow path and power distribution are all designed differently, so if you already know that a rack is where this ends up in a year, it is cheaper to start there. See /products/gpu-servers, and we will help you compare the two on total cost rather than headline spec.

Yes. It arrives built, imaged and tested under load, with the operating system, GPU drivers, CUDA toolchain and your chosen frameworks installed and the versions documented. Dual-GPU builds get particular attention on thermals and driver behaviour under sustained load, because that is where an unvalidated twin-card machine typically fails: not at first boot, but forty minutes into a training run. We would rather find that here than have you find it.

Three or more cards, several concurrent users, or anything with a production availability requirement is server territory rather than workstation territory. At that point you want rack power and cooling, redundancy, out-of-band management and somewhere sensible to put it, none of which a tower provides well. We will say so plainly at quote stage if that is where you are heading, and route you to /products/gpu-servers rather than sell a machine you will replace within the year.