Dell PowerEdge XE9785 AI Server

The Dell PowerEdge XE9785 is a purpose-built AI server engineered around AMD Instinct MI355X accelerators, offering one of the highest GPU-to-rack-unit ratios available in an air-cooled chassis. Designed for organizations demanding massive parallel compute without the infrastructure complexity of liquid cooling, the XE9785 combines a high-bandwidth internal fabric with AMD's CDNA 3 architecture to sustain peak performance across large language model training, fine-tuning, and high-throughput inference workloads. The system launched in Q2 2025 as part of Dell's XE (Extreme Efficiency) portfolio, targeting AI-first data center deployments where power density, thermal management, and accelerator interconnect quality are primary concerns.

At its core, the XE9785 leverages AMD Instinct MI355X GPUs, which are built on CDNA 3 compute architecture and deliver substantial improvements in FP8 and FP16 throughput compared to prior-generation accelerators. Each GPU in the system benefits from high-capacity HBM3E memory, enabling retention of extremely large model parameter sets in accelerator memory without frequent data movement penalties. The server integrates AMD Infinity Fabric links between GPUs to provide low-latency, high-bandwidth peer-to-peer communication essential for tensor-parallel and pipeline-parallel training strategies employed in modern transformer architectures.

The PowerEdge XE9785 is fully integrated into Dell's OpenManage ecosystem, supporting iDRAC9 with Datacenter Telemetry for granular GPU health, thermal, and power monitoring. It is compatible with AMD ROCm software stack, enabling deployment of PyTorch, TensorFlow, and JAX workloads with minimal porting effort from CUDA-based environments. Dell validated the platform with leading MLPerf training benchmarks, making the XE9785 a quantifiable, enterprise-grade choice for organizations scaling generative AI infrastructure.

Ideal for

• Large language model pre-training and fine-tuning for enterprise generative AI applications requiring high HBM capacity per node
• High-throughput inference serving for real-time AI applications including conversational AI, code generation, and multimodal reasoning
• Retrieval-augmented generation (RAG) pipeline acceleration combining dense vector search with GPU-accelerated LLM inference
• Multi-tenant AI model serving in cloud and colocation environments where air-cooling eliminates facility liquid infrastructure requirements
• Scientific computing and simulation workloads such as molecular dynamics, climate modeling, and computational fluid dynamics leveraging AMD ROCm HPC libraries
• Enterprise AI model validation and MLPerf benchmarking for procurement evaluation and capacity planning

Technical specifications

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