Amd Epyc Generative Ai Workloads Server

This AMD EPYC AI tower server is designed for businesses, developers, and research teams building local artificial intelligence applications. Featuring an AMD EPYC 9335 32-core processor, 128GB DDR5 ECC Registered memory, and a PNY NVIDIA RTX A4500 graphics card with 20GB GDDR6 memory, it provides a balanced platform for AI inference, machine learning development, document analysis, and GPU-accelerated data processing.

The system is built around the Tyan Tomcat HX S8050GM4NE-2T motherboard and powered by an AMD EPYC 9335 5th Generation processor with 32 cores, 64 threads, a 3.0GHz base frequency, and a 210W TDP. Its multi-core architecture supports dataset preparation, parallel processing, application services, and background tasks alongside GPU workloads. This combination is suitable for teams developing and deploying AI applications on a dedicated server.

The PNY NVIDIA RTX A4500 GPU provides 20GB of dedicated GDDR6 graphics memory for CUDA-accelerated computing. It supports compatible machine learning frameworks and applications for language model inference, image generation, computer vision, embeddings, and speech processing. Model capacity and performance depend on precision, context length, batch size, and software requirements. Quantized language models and parameter-efficient fine-tuning of smaller models can be configured within the available GPU memory.

With 128GB DDR5 ECC Registered server memory, the system provides capacity for dataset loading, preprocessing, application caching, and supporting services. ECC memory helps detect and correct supported memory errors, contributing to reliable operation during extended workloads. System RAM supports the overall AI workflow, while the GPU’s dedicated 20GB memory determines how much model data can remain on the graphics card during processing.

Two 480GB 2.5-inch SATA enterprise server SSDs provide 960GB of combined raw capacity for Ubuntu Linux Server, development tools, containers, and application configuration. These drives can be configured as a RAID1 mirror, providing approximately 480GB of capacity while allowing continued operation following the failure of one system SSD.

Two 3.84TB M.2 2280 enterprise server SSDs provide 7.68TB of combined raw capacity for AI models, training datasets, vector indexes, project files, and checkpoints. A mirrored configuration provides approximately 3.84TB before formatting and filesystem overhead, with protection against the failure of one drive. Separating system storage from working data simplifies administration and keeps dedicated storage available for active AI projects. Important datasets and project results should also be backed up to a separate device.

The hardware is housed in an InWin IW-PL052 tower chassis. A dedicated 4U SP5 CPU Cooling Heatsink Fan Assembly cools the AMD EPYC processor, while a 1000W enterprise server power supply powers the configured components. The chassis airflow and SSD cooling are configured to support sustained CPU and GPU workloads, with component clearances and power connections checked during assembly.

Ubuntu Linux Server 26.04 LTS 64-bit comes pre-installed, providing a flexible foundation for AI development, automation, and containerized applications. Compatible NVIDIA drivers, CUDA libraries, and GPU-enabled frameworks can be configured for your workload. The server can support tools such as PyTorch, TensorFlow, and Docker when installed with versions compatible with the operating system and RTX A4500 GPU.

This NVIDIA GPU AI server is suitable for local AI assistants, retrieval-augmented generation applications, document search, image analysis, and machine learning experimentation. It enables organizations to host models and process datasets on infrastructure they control. Its combination of CPU resources, ECC memory, GPU acceleration, and dedicated SSD storage supports development and deployment on a single platform.

Our server configurator allows you to select compatible memory upgrades, larger enterprise SSDs, and alternative graphics cards to match your AI requirements. GPU memory, storage capacity, and processing resources can be tailored to the models you plan to run, the size of your datasets, and the number of concurrent users.

Every server is professionally assembled, configured, and tested before shipment. Quality assurance includes checks of processor cooling, ECC memory, GPU operation, SSD storage, power delivery, and operating system configuration. Assembly and testing are included at no additional cost, and each system is backed by warranty coverage and professional technical support.