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VRLA Tech AMD EPYC 2U GPU Server for Large Language Models
VRLA Tech AMD EPYC 2U GPU Server for Large Language Models
VRLA Tech AMD EPYC 2U GPU Server for Large Language Models
VRLA Tech AMD EPYC 2U GPU Server for Large Language Models
VRLA Tech AMD EPYC 2U GPU Server for Large Language Models
VRLA Tech AMD EPYC 2U GPU Server for Large Language Models
VRLA Tech AMD EPYC 2U GPU Server for Large Language Models
VRLA Tech AMD EPYC 2U GPU Server for Large Language Models
VRLA Tech AMD EPYC 2U GPU Server for Large Language Models
VRLA Tech AMD EPYC 2U GPU Server for Large Language Models
VRLA Tech AMD EPYC 2U GPU Server for Large Language Models
VRLA Tech AMD EPYC 2U GPU Server for Large Language Models
VRLA Tech AMD EPYC 2U GPU Server for Large Language Models
VRLA Tech AMD EPYC 2U GPU Server for Large Language Models
Purchase with confidence, 3 year warranty from the date of delivery, lifetime support
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VRLA Tech AMD EPYC 2U GPU Server for Large Language Models

$66,949.96

High-Density AI Inference & Fine-Tuning Purpose-built for enterprise-grade AI, the VRLA Tech…

AMD EPYC 9004 PROCESSOR
High-Density AI Inference & Fine-Tuning

Purpose-built for enterprise-grade AI, the VRLA Tech AMD EPYC 2U GPU Server is a compact, high-density solution engineered for large language model (LLM) inference, fine-tuning, and edge deployment. Powered by the AMD EPYC 9375F (32 cores, 3.8GHz) and equipped with 4× NVIDIA RTX PRO 6000 Blackwell Max-Q GPUs, this 2U server delivers up to 384GB of combined GPU VRAM — ideal for 70B parameter FP16 inference, LoRA fine-tuning, and low-latency AI serving.
This platform is optimized for production AI, supporting NVIDIA RTX PRO Blackwell and L40S for both foundation model deployment and multi-modal AI workloads (vision + language). With 768GB DDR5-6400 ECC RAM, ultra-fast PCIe Gen5 bandwidth, and dual 240V redundant power, it’s engineered for reliability in research labs, cloud providers, enterprises, and AI startups. Fully rackmountable in just 2U, this system packs extreme power into a space-efficient chassis — making it the perfect LLM inference server, API deployment backend, or AI edge compute node for OpenAI, HuggingFace, TensorRT-LLM, vLLM, or FastAPI integrations.
Weight 40 lbs
Dimensions 26 × 14 × 27 in

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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.
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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.
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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.
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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.
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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.
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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.
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