Dell Technologies has introduced the PowerEdge XE7740 server, featuring Intel Gaudi 3 PCIe accelerators, marking the company’s entry as the first to market with an integrated configuration built around Intel’s latest AI acceleration hardware. The launch underscores the ongoing push to expand on-premises AI infrastructure options for enterprises seeking scalable, cost-efficient performance.
The 4U PowerEdge XE7740 combines the design efficiency of Dell’s R-Series with the compute and scalability of the XE-Series. It is engineered for a range of AI workloads, including model fine-tuning, high-performance inferencing, and multimodal applications that require both flexibility and consistent performance. Its modular setup allows up to eight double-wide or PCIe accelerators, and configurations supporting either eight individual Gaudi 3 units or two bridged groups of four.
The 4-way Gaudi 3 PCIe bridging delivers 1,200 GBps combined throughput for accelerator-to-accelerator communication over 18 200GbE interfaces using RDMA over Converged Ethernet (RoCE v2). This setup enables faster interconnect speeds critical for training large models and managing data-intensive workloads. The XE7740 also supports up to a 1:1 accelerator-to-network interface card ratio across eight full-height PCIe slots and an integrated OCP networking module, allowing for highly flexible networking architecture.
Built for data centers operating around 10kW racks, the XE7740 integrates seamlessly with existing air-cooled infrastructure. Its Smart Cooling system helps maintain efficiency without requiring major retrofits for power or cooling, reducing deployment complexity for enterprises upgrading AI capabilities within traditional environments.
Designed to handle a wide spectrum of AI workloads, the server supports large language model inferencing and fine-tuning, multimodal AI for image and speech recognition, and data-heavy tasks in healthcare, finance, manufacturing, and retail. The Gaudi 3 PCIe accelerators are compatible with frameworks such as PyTorch and platforms like Hugging Face, allowing developers to fine-tune or infer models more efficiently.
From a cost and operational perspective, the XE7740 aims to make enterprise AI adoption more accessible. It provides a strong price-to-performance ratio and modular scalability, giving organizations flexibility to grow capacity incrementally. By reducing dependency on cloud-based pay-as-you-go compute and minimizing egress costs, it helps businesses keep sensitive workloads on-premises without sacrificing performance or efficiency.
Beyond raw power, the XE7740’s adaptability makes it well-suited for organizations seeking predictable, sustainable AI infrastructure. Its compatibility with leading AI models—including Llama, Deepseek, Qwen, and Falcon—offers immediate applicability across use cases. For enterprises pursuing long-term AI integration, the PowerEdge XE7740 positions itself as a balanced option for performance, scalability, and energy efficiency within existing data center constraints.
