Lenovo ThinkSystem SR650 V3 with NVIDIA L4 24GB PCIe

The Lenovo ThinkSystem SR650 V3 (7D76CTO2WW) is a 2U dual-socket rack server engineered for demanding enterprise, datacenter, and AI inference workloads. Built on the Intel Xeon Scalable 4th Generation (Sapphire Rapids) processor platform, the SR650 V3 supports up to two processors and delivers a high-bandwidth memory and I/O architecture optimized for GPU-accelerated computing. When configured with the NVIDIA L4 24GB PCIe GPU, the system targets a broad spectrum of AI and accelerated computing tasks, combining the stability and manageability of Lenovo's ThinkSystem server portfolio with NVIDIA's Ada Lovelace generation inference silicon.

The NVIDIA L4 24GB PCIe adapter installed in this configuration is a 72-watt single-slot GPU based on the NVIDIA Ada Lovelace architecture, featuring 24 GB of GDDR6 ECC memory and 58.9 TOPS of INT8 performance. The L4 is purpose-built for energy-efficient AI inference, video transcoding, and professional visualization in space- and power-constrained datacenter environments. Its low TDP makes it compatible with standard PCIe slots without requiring supplemental power connectors, enabling high-density GPU deployments within the SR650 V3's multiple PCIe Gen 5 expansion slots. The combination supports NVIDIA's full software ecosystem including CUDA, TensorRT, and NVIDIA AI Enterprise.

The ThinkSystem SR650 V3 platform supports up to 32 DIMM slots accommodating DDR5 memory at speeds up to 4800 MT/s, PCIe Gen 5 connectivity, and Lenovo's XClarity management suite for lifecycle, firmware, and telemetry management. The system is designed to integrate into existing enterprise IT environments with support for Lenovo Neptune liquid cooling options and is well suited for organizations across UAE, GCC, EMEA, and APAC regions seeking scalable, GPU-accelerated rack infrastructure for production AI and data-intensive operations.

Ideal for

• AI inference serving for natural language processing and computer vision models in production datacenter environments
• High-density video transcoding and streaming media processing leveraging NVIDIA L4 NVENC/NVDEC hardware acceleration
• Enterprise virtual desktop infrastructure (VDI) and GPU-accelerated remote workstation delivery via NVIDIA vGPU software
• Edge AI and real-time analytics pipelines requiring energy-efficient, low-latency GPU compute within standard power budgets
• Model deployment and inference optimization using NVIDIA TensorRT within MLOps and AI platform workflows
• Scientific and technical computing workloads requiring CUDA-based acceleration on a managed, enterprise-grade server platform

Technical specifications

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