Dell PowerEdge XE9680 with 8× NVIDIA H100 GPUs: Special Offer

3 days ago
4 min read

Updated: 2 days ago

The Dell PowerEdge XE9680 offered here is a 6U enterprise AI server configured with 8× NVIDIA H100 80GB SXM GPUs, dual Intel Xeon Platinum 8462Y+, and 2TB DDR5 memory. This is a fixed, validated configuration available as a refurbished, fully tested, deployment-ready system.

Dell XE9680 with 8× NVIDIA H100

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Configuration Overview: Dell PowerEdge XE9680 with 8× NVIDIA H100 SXM

This Dell PowerEdge XE9680 configuration is built around an 8-GPU NVIDIA HGX H100 80GB SXM platform fully interconnected with NVIDIA NVLink, designed for sustained AI training, distributed workloads, and GPU-accelerated HPC.

It is designed for:

Sustained multi-GPU AI training
Distributed model parallelism and data parallelism
Multi-node cluster scaling using high-speed fabric

The servers offered are based on a fixed, fully supported configuration selected for stability, compatibility, and real-world deployment. Component choices reflect validated enterprise configurations rather than theoretical maximum-spec builds.

Full Configuration: Dell PowerEdge XE9680 with 8× NVIDIA H100 GPUs

Base System: Dell PowerEdge XE9680 6U Rack Server

Component	Details	Why it matters
Server / Chassis	Dell PowerEdge XE9680 (6U)	Purpose-built enterprise AI platform
Front Bays	8× SFF NVMe	High-density local NVMe storage
Bay Config	2XR8X04	Validated NVMe backplane configuration
PCIe	Up to 10× PCIe Gen5 x16 slots	High-bandwidth expansion for networking and accelerators

GPUs: 8× NVIDIA HGX H100 80GB SXM

Component	Details	Why it matters
GPUs	8× NVIDIA HGX H100 80GB SXM	High-performance AI training acceleration
GPU Memory	80GB HBM3 per GPU	Supports large models and large batch sizes
Interconnect	NVIDIA NVLink (HGX fully interconnected topology)	High-bandwidth GPU-to-GPU communication

Each GPU supports up to 700W TDP. The HGX SXM architecture enables:

Direct NVLink connectivity between GPUs
Reduced scaling overhead in multi-GPU training
Efficient collective communication operations

This platform is optimized for large transformer and foundation model workloads.

CPUs: 2× Intel Xeon Platinum 8462Y+

Component	Details	Why it matters
CPUs	2× Intel Xeon Platinum 8462Y+	Host compute and orchestration
Base Frequency	2.8 GHz	Sustained compute baseline
Max Turbo Frequency	Up to 4.1 GHz	Higher performance for burst workloads

CPUs handle:

Data ingestion and preprocessing
Job scheduling and orchestration
Storage and network coordination

In AI systems of this class, GPUs deliver primary compute while CPUs maintain pipeline efficiency.

Memory: 2048GB DDR5 (32× 64GB PC5-4800)

Component	Details	Why it matters
Installed Memory	2048GB (32× 64GB)	Supports large dataset handling
DIMM Rating	PC5-4800 (DDR5-4800 DIMMs)	Manufacturer-rated speed
Operating Speed	4400 MT/s (2 DIMMs per channel)	Actual supported speed in this configuration

Because this system uses 32 DIMMs across two sockets (2 DIMMs per channel), memory operates at 4400 MT/s according to Intel and Dell specifications for 4th Gen Xeon Scalable processors. This configuration provides high memory capacity while maintaining validated platform stability.

Storage: 2× 7.68TB NVMe U.2 Gen4 SSDs

Component	Details	Why it matters
Installed Drives	2× 7.68TB NVMe Gen4 2.5"	High-throughput data staging
Chassis Capability	8× SFF NVMe bays	Expansion-ready storage density
RAID Support	PERC H965i supported	Enterprise RAID options available

With 8 NVMe bays, the system can support significantly larger storage capacity (e.g., up to ~122TB using 8× 15.36TB drives).

Local NVMe storage is commonly used for:

Dataset staging
Checkpoints
Scratch space
High-speed caching

Networking: 8× Mellanox MT2910 (ConnectX-7)

Component	Details	Why it matters
High-Speed Adapters	8× Mellanox MT2910 (ConnectX-7)	Cluster-scale communication
Protocol Support	InfiniBand / Ethernet	Flexible cluster fabric options
Port Speeds	Up to 400Gb/s per adapter	High-bandwidth distributed training
Onboard Ethernet	2× Broadcom 5720 Dual Port 1GbE	Management networking

ConnectX-7 adapters are commonly deployed in modern AI clusters to support:

Distributed training
RDMA
Low-latency node-to-node communication

Management

Component	Details	Why it matters
Remote Management	iDRAC 9 Enterprise (reset to defaults)	Out-of-band monitoring and lifecycle management

Supports remote console access, firmware updates, and power control.

Power & Cooling

Component	Details	Why it matters
Power Supplies	6× 2800W PSU	Supports sustained high GPU load
Cooling	High-performance air cooling (mid-tray + rear fan modules)	Designed for high-TDP GPU operation
Estimated Power Draw	~8–10kW under load	Datacenter provisioning requirement

8× NVIDIA H100 SXM GPUs (up to 700W each) plus CPUs and networking require appropriate datacenter-grade power and cooling infrastructure.

Platform Overview: Dell PowerEdge XE9680 with 8× NVIDIA H100

The Dell PowerEdge XE9680 is engineered for AI infrastructure environments where:

GPU density
Thermal management
High-speed networking
Remote lifecycle control

are required for sustained production workloads.

Use Cases: Dell PowerEdge XE9680 with 8× NVIDIA H100 GPUs

Large language model training
Foundation model development
Multi-node distributed AI training
HPC simulation workloads
Research and scientific computing

Testing, Condition, and Warranty: Dell PowerEdge XE9680 with 8× NVIDIA H100 GPUs

Condition: Refurbished, fully tested.

Testing includes:

CPU, memory, and GPU validation
Storage and NVMe verification
Network adapter testing
Stability verification under load

Warranty:

3-Year hardware warranty included
Fully tested and validated prior to delivery
Deployment-ready system configuration
Extended support options available upon request
Custom service agreements can be arranged if required

This Dell PowerEdge XE9680 configuration is a purpose-built AI infrastructure node designed for organizations that require dense multi-GPU compute, sustained AI training performance, high-bandwidth cluster networking, and datacenter-grade power and cooling for modern GPU clusters.