RTX 5090 GPU Server
Cost-effective rackmount GPU density for inference and development workloads.
We help you choose, configure, and deliver the right system. No obligation.
Configuration at a Glance
Tailored per engagement. Full technical overview below.
Configuration Options
Core specifications for this system. Every component is configurable to your workload, so request a quote for a tailored build.
4–8× NVIDIA RTX 5090 (32GB each)
Dual AMD EPYC or Intel Xeon
Up to 1.5TB ECC
Hot-swap NVMe array
Overview
The RTX 5090 GPU Server packs multiple RTX 5090 GPUs into a rack server, offering high GPU density at consumer-GPU economics. Nexus Compute specifies these systems for teams whose workloads (inference, development, and rendering) benefit more from GPU count and value than from data-center GPU features. The trade here is memory and interconnect, not arithmetic throughput. Each card carries 32GB, so a model and its working set have to fit within a single card to run well: consumer-class GPUs have no NVLink bridge, and GPU-to-GPU traffic crosses PCIe, which is roughly an order of magnitude narrower than the interconnect in a data-center node. That makes this a strong platform for many independent replicas of a model that fits in 32GB, and a poor one for a single model that does not. In practice that covers most production inference, most rendering, and development environments mirroring a larger production stack. Cooling is the second consideration: these cards are physically dense and air-hungry, so chassis, card spacing, and fan curves are validated as a set rather than assumed to work.
Who This Solution Is For
Business Benefits
More GPUs per dollar
RTX 5090 cards deliver strong density and value for workloads that do not require data-center GPU memory or ECC.
Rack-grade reliability
Server chassis, redundant power, and remote management bring data-center operations to consumer GPUs.
Ideal for inference and dev
High GPU count suits parallel inference, rendering, and development/staging fleets.
Sourced and validated
We validate multi-GPU thermals and drivers so the system is production-stable on arrival.
Typical Business Use Cases
High-throughput inference serving for internal applications
GPU rendering and content generation farms
Development and staging environments at GPU density
Cost-optimized parallel batch processing
Running many independent replicas of a model that fits one GPU
Batch rendering, transcoding, and offline generation fleets
Industry Applications
Technical Overview
A rack platform housing multiple RTX 5090 GPUs with dual server CPUs, ECC memory, high-speed networking, redundant power, and out-of-band management, engineered for stable multi-GPU operation. Because each GPU works largely independently in this platform, the host has to support all of them at once: a generous PCIe lane budget so cards are not sharing bandwidth behind a switch, enough cores for per-replica preprocessing, and system memory sized against the number of concurrent workers rather than against aggregate GPU memory. The storage profile differs from training: model weights are read once and then resident, so the priority is a local NVMe tier holding the model catalogue and container images for fast cold starts rather than sustained streaming throughput, with bulk capacity behind it under /products/storage. Standard 25/100GbE is generally sufficient here; low-latency RDMA fabrics only become relevant if you later intend to split a single model across cards or nodes, and those options are under /products/networking.
| GPU Capacity | 4–8× NVIDIA RTX 5090 (32GB each) |
| CPU | Dual AMD EPYC or Intel Xeon |
| System Memory | Up to 1.5TB ECC |
| Storage | Hot-swap NVMe array |
| Networking | 25/100GbE |
| Management | IPMI / out-of-band |
| Power | Redundant N+1 PSUs |
| Form Factor | 4U rackmount |
| GPU Memory Bandwidth (RTX 5090) | 1,792 GB/s, 512-bit GDDR7 |
| GPU TDP (RTX 5090) | 575W (600W PCIe Gen5 12V-2x6 connector) |
| CUDA Cores (RTX 5090) | 21,760 |
| GPU Architecture | NVIDIA Blackwell |
Specifications are indicative and configured to each engagement. Request a quote for a configuration tailored to your requirements.
Warranty, Support & Fulfillment
Every system ships from an authorized channel, configured and tested, with the documentation enterprise buyers need: genuine product, backed by the full manufacturer warranty.
Enterprise Warranty
Full manufacturer warranty with optional on-site, next-business-day support and extended coverage.
Authorized Channel
Sourced through Tier-1 distribution and OEM partners (never grey market). Asset & warranty records included.
Lead Time & Deployment
48-hour quotes, then configured, burn-in tested, and delivered on a committed schedule.
Nationwide Fulfillment
Coordinated logistics, rack-and-stack, and delivery wherever your infrastructure lives.
Frequently Asked Questions
Why choose RTX 5090 over H100 in a server?
RTX 5090 offers better raw price-performance for many inference, rendering, and development workloads. H100/H200 win where data-center memory bandwidth, ECC, or NVLink at scale matter. We advise based on your workload.
Is it suitable for training?
It can train smaller models well. For large-model training where GPU interconnect bandwidth is critical, we recommend our H100/H200 servers or clusters.
How many GPUs can it hold?
Typically four to eight RTX 5090s depending on the chassis and power configuration we specify for your facility.
What lead time should I expect?
Consumer-class GPUs are ordinarily easier to source than data-center parts and are not on the same allocation cycle, so lead times tend to be shorter and more predictable. Supply can still tighten when a card is newly launched or in wide demand, so we confirm the current position at quote rather than quoting from a catalogue.
What power and cooling does a dense consumer-GPU node need?
More than the card count suggests. High-end consumer GPUs draw heavily and sit close together, so an eight-card node is a multi-kilowatt load in a chassis that has to move a large volume of air through tightly spaced cards. We validate thermals with the exact cards and chassis rather than assuming, and confirm your rack can both supply the circuit and remove the heat before the order is placed.
What warranty and support applies to consumer GPUs in a server?
The platform ships through authorized channels with the full manufacturer warranty. Consumer-class GPUs carry consumer warranty terms rather than the data-center support programs attached to H100-class parts, which is one of the real trade-offs in choosing them. We set out exactly what covers each part of the configuration in the quote so there is no ambiguity later.
Hardware Assistance
Configure the RTX 5090 GPU Server with Nexus Compute
Tell us your requirements and a hardware specialist will help you specify, configure, and quote the right system, typically within two business days. No obligation.