Dell PowerEdge R760xa 4-GPU Server Configured with L40S 48GB (4× GPU, 2× Xeon Scalable 6)

The Dell PowerEdge R760xa is a 2U rack server engineered specifically for GPU-intensive enterprise workloads, supporting up to four double-width GPUs in a thermally optimized chassis. Configured with four NVIDIA L40S 48GB GPUs, this system delivers a combined 192 GB of GPU memory alongside dual 5th-generation Intel Xeon Scalable (Xeon 6) processors, providing a high-throughput compute platform suited to large-scale AI inference, model training, and data science pipelines. The R760xa chassis incorporates dedicated GPU airflow zones and high-capacity power subsystems to sustain continuous full-load GPU operation across all four accelerators simultaneously.

The NVIDIA L40S is built on the Ada Lovelace architecture and combines FP32, TF32, FP16, BF16, INT8, and FP8 precision support in a single GPU, making it exceptionally versatile across both training and inference stages of AI development. Each L40S card carries 48 GB of GDDR6 ECC memory and includes dedicated hardware for ray tracing and AV1 encoding, extending the platform's utility beyond pure compute into professional visualization and media rendering. The four-GPU configuration connected through PCIe Gen 5 fabric to the dual Xeon 6 host processors ensures low-latency data movement between host memory and GPU framebuffers, which is critical for large-batch inference and multi-model serving environments.

As a Dell PowerEdge platform, the R760xa integrates the iDRAC9 with OpenManage for lifecycle management, remote monitoring, automated firmware updates, and integration with enterprise orchestration stacks including VMware vCenter, Microsoft SCVMM, and Ansible. The server is deployable in standard 19-inch data center racks and is compatible with Dell's OpenManage Enterprise and Apex infrastructure frameworks, supporting organizations that require centralized fleet management across mixed AI and general-purpose server estates in UAE, GCC, EMEA, and APAC data center environments.

Ideal for

• Large-scale generative AI inference serving, including large language model (LLM) deployments requiring high GPU memory capacity per node
• Enterprise AI model fine-tuning and training on domain-specific datasets where high FP8/BF16 throughput accelerates iteration cycles
• Multi-tenant GPU virtualization using NVIDIA vGPU software to provide isolated GPU slices to multiple VM or container workloads
• Professional 3D visualization and GPU-accelerated rendering pipelines for engineering, media, and design workflows leveraging Ada Lovelace RT cores
• High-throughput video transcoding and AV1 encoding at scale for broadcast, streaming, and media archive workflows
• Data analytics and HPC workloads requiring large GPU memory pools for in-memory graph analytics, seismic processing, or financial risk modeling

Technical specifications

Available from Omnixon Global. Submit an RFQ and our team will confirm configuration and availability for your order.