Scale AI at data center density.

An LLM server is a purpose-built GPU server designed to train, fine-tune, and serve large language models at production scale. VRLA Tech's Scale-stage LLM servers are AMD EPYC rack systems with 4 to 8 NVIDIA GPUs, high-bandwidth ECC memory, and 24/7 data center operation — engineered for frontier-scale model training, high-throughput inference, and enterprise AI deployment. These systems sit above team-shared Deploy workstations in the deployment pathway and support cluster expansion for organizations scaling to multi-node training.

Move to Scale when production workloads, customer-facing inference, or model training at frontier scale demand 24/7 data center operation. Common triggers include: needing 8 GPUs in a single node, multi-node cluster training, sub-second inference SLAs, regulatory requirements for dedicated infrastructure, or outgrowing Deploy-stage multi-user Threadripper PRO capacity. Scale systems drop into standard 42U racks with InfiniBand NDR fabric support for multi-node expansion.

Choose the 2U 4-GPU EPYC server for density-optimized deployments where you want maximum GPUs per rack unit and plan to run multiple nodes. Choose the 4U 8-GPU EPYC server when you need maximum GPUs per node for very large models, frontier-scale training, or workloads requiring NVLink interconnect. The 4U chassis also offers better thermal headroom for sustained full-power operation across all 8 GPUs.

AMD EPYC 9005 (Turin) delivers up to 192 cores per socket, 12-channel DDR5 ECC memory, and 128 PCIe 5.0 lanes per CPU — substantially more memory bandwidth and PCIe lanes than comparable Intel Xeon 6 configurations. For LLM training and inference where GPU feeding and memory throughput are the primary bottlenecks, EPYC's superior I/O and memory subsystem translates directly to higher training throughput and lower inference latency. Intel Xeon remains strong for workloads requiring specific ISA features like AMX.

Scale servers ship with NVIDIA RTX PRO 6000 Blackwell Server GPUs — the passive-cooled data center variant with 96 GB HBM3e and NVLink support. We also configure NVIDIA H200 (141 GB HBM3e), H100 NVL, L40S, and AMD Instinct MI300X depending on workload. Frontier-scale training typically specifies RTX PRO 6000 Server or H200 with InfiniBand NDR fabric between nodes.

Yes. Both Scale-stage servers fit standard 19-inch 42U racks with the included rack rails. A fully loaded 4U 8-GPU server draws 5,000 to 6,000 watts and typically requires two 30A 208V circuits per node. Rack-level considerations include rear-door heat exchangers or hot-aisle containment above 10 kW/rack, redundant 208V PDUs, and network fabric — we help customers spec the full rack and power footprint before order.

Yes. Every Scale server is configurable with NVIDIA ConnectX-7 or ConnectX-8 network adapters supporting 200, 400, or 800 Gbps InfiniBand NDR or Ethernet fabric for low-latency multi-node training. We commonly deliver 4, 8, and 16 node clusters pre-configured with Slurm or Kubernetes, matched CUDA and NCCL versions, and validated multi-node NCCL performance before shipping.

Yes. Every VRLA Tech system across Develop, Deploy, and Scale ships with matching NVIDIA driver, CUDA, cuDNN, TensorRT, PyTorch, and framework versions. Code and containers developed on a Develop workstation deploy to a Scale server with no rebuild, which is the primary advantage of running the full deployment pathway on a single engineering team.

Standard Scale servers ship in 3 to 6 weeks from order confirmation, which includes build, 72 to 96 hour burn-in testing, thermal validation, and packaging. Multi-node cluster orders and configurations with specialty GPUs may extend to 6 to 10 weeks depending on component availability. We give you a firm timeline upfront at order confirmation and GPU allocations through NVIDIA Partner Network where applicable.

VRLA Tech delivers comparable AMD EPYC rack servers in 3 to 6 weeks versus the 16 to 24 week OEM average, typically at 20 to 35 percent lower pricing than equivalent Dell PowerEdge XE9680 or HPE Cray XD configurations. Every system includes lifetime US engineer support at no extra cost — you speak directly with the engineers who built your system, not through tiered support contracts.

Yes, and most customers do exactly this. Start with one or two Scale nodes for initial production workloads, then add matched nodes as demand grows. We maintain CPU, motherboard, and networking SKU consistency across production runs so future nodes match exactly — critical for homogeneous cluster performance and Slurm scheduling.

Every VRLA Tech Scale-stage system 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. For production-critical deployments, we also offer 4-hour and next-business-day on-site response SLAs in major US metros as an add-on.