Rack Mount · Built in LA

Enterprise GPU servers for AI and research.

1U, 2U, and 4U rackmount configurations with up to 8× NVIDIA RTX PRO 6000 Blackwell Server and AMD EPYC 9005. Hand assembled in Los Angeles, 48 to 72 hour burn in tested, 3 year parts warranty with lifetime US based engineer support.

★★★★★ 4.9/5  ·  1,240+ Reviews Ships Worldwide
NVIDIA RTX PRO 6000 Blackwell Server
VRLA Tech flagship 4U GPU server: AMD EPYC 9005 with 8x NVIDIA RTX PRO 6000 Blackwell Server
Flagship · 4U Rack EPYC 9005 · 8× RTX PRO 6000
GPU VRAMUp to 768 GB
Starting at$44,999
Configure →
Deployed by Fortune 500, Research Labs, Federal Agencies
General Dynamics Los Alamos National Laboratory Johns Hopkins University The George Washington University Miami University

3 year warranty.
Lifetime support.

Talk to the same US based engineers who built your server, for the life of the system.

3 Years
Parts Warranty
Lifetime
US Engineer Support
48–72h
Burn In Per Build
Server Questions

Racks, power, networking, support

Answers to the most common questions about VRLA Tech GPU servers. Still have questions? Talk to our engineers.

What types of servers does VRLA Tech build?

VRLA Tech builds custom 1U, 2U, and 4U rackmount GPU servers, LLM inference servers, AI training clusters, HPC compute nodes, storage servers, and virtualization hosts. Configurations scale from single-socket CPU-only boxes up to dual EPYC nodes with 8× NVIDIA RTX PRO 6000 Blackwell Server. Every server is spec'd to your workload — tell us what you're running and we'll size the rack.

How many GPUs can fit in one server?

Our flagship 4U chassis holds up to 8× NVIDIA RTX PRO 6000 Blackwell Server for 768 GB of total VRAM, the highest GPU density available in a single workstation-class server. 2U chassis hold 2–4 GPUs for denser racks and shared inference deployments. 1U chassis hold up to 2 GPUs for edge and colocation deployments where rack-unit budget is tight. For multi-node deployments above 8 GPUs, we build InfiniBand-connected clusters at any scale.

What CPUs do you use in GPU servers?

Our standard GPU server platform is AMD EPYC 9005-series, which offers up to 256 cores per socket, 24 DDR5 memory channels, and 128 PCIe 5.0 lanes per socket — the maximum bandwidth available for multi-GPU configurations. For customers standardizing on Intel, we also build on Xeon Scalable 5th and 6th Generation. CPU choice is driven by PCIe lane count, memory bandwidth, and any ISV certification requirements for your software stack.

What networking options do you offer?

Every server ships with dual 10 GbE onboard. For AI and HPC workloads, we add NVIDIA ConnectX-7 or ConnectX-8 NICs supporting 100 GbE, 200 GbE, or 400 GbE Ethernet, plus InfiniBand NDR (400 Gb/s) for multi-node GPU clusters. For storage-heavy deployments we spec dedicated 25 GbE or 100 GbE fabric separate from the compute network. All networking is sized to the workload at order time.

What storage configurations do you support?

Server storage is configured per workload: enterprise NVMe (Gen4 or Gen5) for hot tier, SATA/SAS SSD for warm tier, and 18–24 TB helium-sealed HDDs for bulk capacity. Most AI servers ship with at least 2× NVMe in RAID 1 for the OS plus 4–8 additional NVMe drives for datasets, scratch, and checkpoints. For multi-node clusters we integrate parallel file systems — Lustre, BeeGFS, or WekaIO — sized to sustain 2–4 GB/s per GPU.

Do your servers support remote management?

Yes. Every VRLA Tech server ships with IPMI 2.0, a dedicated BMC network port, iKVM over LAN, serial over LAN, and redundant management firmware. There are no license fees and no paywalled features — everything works out of the box. Redfish API access is standard for fleet automation and integration with tools like Ansible, Terraform, and MAAS.

Can you pre-install our OS and software stack?

Yes. We pre-install Ubuntu LTS, RHEL, Rocky Linux, Debian, Proxmox, or VMware ESXi, along with NVIDIA drivers, CUDA, container runtime (Docker or Podman), vLLM, TensorRT-LLM, PyTorch, or any framework you specify. For fleet deployments we can match your golden image and provisioning keys before shipping, so servers arrive ready to join your infrastructure on first boot.

What are the power and cooling requirements?

An 8× RTX PRO 6000 Blackwell Server server draws 4,000 to 5,200 watts at full load and requires 208V input with dual 3,000W or 3,200W redundant PSUs. Heat output is 15,000 to 18,000 BTU/hr per chassis. For rack deployments we spec PDUs, rack power density (typically 20–30 kW per rack for GPU servers), and hot aisle layout as part of the order. Liquid cooling is available for dense multi-GPU configurations.

What's the lead time on a custom GPU server?

Standard single-node GPU servers ship in 7 to 10 business days from order confirmation, which includes build, 48 to 72 hour burn-in testing, thermal validation, and packaging. Multi-node clusters with InfiniBand fabric typically ship in 4 to 8 weeks depending on node count and storage configuration. Complex custom builds or specialty chassis may add lead time — we give you a firm timeline upfront at order confirmation.

Do you deliver pre-racked and cabled?

Yes. For fleet and cluster deployments we rack, cable, and cable-manage in our Los Angeles facility before shipping. You receive the rack ready to power on. On-site deployment is available if you need our engineers to install the rack in your facility, commission the fabric, and validate first-workload performance.

What warranty and support options are available?

Every VRLA Tech server includes a 3-year parts warranty and lifetime US-based engineer support at no extra cost. You speak directly with the engineers who built your system — no tiered support contracts, no call centers, no paid upgrades. If something fails in warranty, we replace the part and cover shipping.

Do you accept government and enterprise procurement?

Yes. VRLA Tech accepts purchase orders, ACH and wire transfers, and GSA payment processes for federal, state, and enterprise customers. We work directly with procurement teams on net-30 and net-60 terms, blanket POs, and multi-year contracts. Financing is also available through Affirm and Bread Pay on eligible single-server configurations.

How do VRLA Tech servers compare to Dell, HPE, or Supermicro direct?

VRLA Tech builds every server to your exact workload with no locked SKUs, typically delivers in 7–10 business days versus the 16–24 week OEM average, and includes lifetime US engineer support at no extra cost. Our pricing usually runs 20–30% below equivalent Dell PowerEdge or HPE ProLiant configurations without cutting component quality. Unlike Supermicro direct, you get a named engineering team, burn-in testing, and a single point of contact through deployment and beyond.

Can I start with one server and scale to a cluster later?

Yes. Many customers start with a single 4U GPU server for development and fine-tuning, then add nodes and InfiniBand fabric as production workloads grow. We design initial deployments with cluster expansion in mind — matching node specs, reserving fabric capacity, and sizing shared storage so you can scale without forklift-upgrading. For a planned cluster path, talk to us upfront so we can spec accordingly.

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U.S Based Support
Based in Los Angeles, our U.S.-based engineering team supports customers across the United States, Canada, and globally. You get direct access to real engineers, fast response times, and rapid deployment with reliable parts availability and professional service for mission-critical systems.
Expert Guidance You Can Trust
Companies rely on our engineering team for optimal hardware configuration, CUDA and model compatibility, thermal and airflow planning, and AI workload sizing to avoid bottlenecks. The result is a precisely built system that maximizes performance, prevents misconfigurations, and eliminates unnecessary hardware overspend.
Reliable 24/7 Performance
Every system is fully tested, thermally validated, and burn-in certified to ensure reliable 24/7 operation. Built for long AI training cycles and production workloads, these enterprise-grade workstations minimize downtime, reduce failure risk, and deliver consistent performance for mission-critical teams.
Future Proof Hardware
Built for AI training, machine learning, and data-intensive workloads, our high-performance workstations eliminate bottlenecks, reduce training time, and accelerate deployment. Designed for enterprise teams, these scalable systems deliver faster iteration, reliable performance, and future-ready infrastructure for demanding production environments.
Engineers Need Faster Iteration
Slow training slows product velocity. Our high-performance systems eliminate queues and throttling, enabling instant experimentation. Faster iteration and shorter shipping cycles keep engineers unblocked, operating at startup speed while meeting enterprise demands for reliability, scalability, and long-term growth today globally.
Cloud Cost are Insane
Cloud GPUs are convenient, until they become your largest monthly expense. Our workstations and servers often pay for themselves in 4–8 weeks, giving you predictable, fixed-cost compute with no surprise billing and no resource throttling.