H6614-70

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2. Since inventories and prices may fluctuate to some extent, the sales manager is going to reconfirm the order and let you know if there are any updates.

Product Specification: H6614-70

Category	Parameter	Specification / Value	Notes / Conditions
General	Model Number	H6614-70
	Product Name	[e.g., Liquid-Cooled AI Training Appliance with 4x A100 80GB]	Please specify
	Product Type	[e.g., 4U AI Accelerated Server, Pre-validated Solution]
	Form Factor	4U Rackmount
	Solution SKU	Pre-configured and validated for Large Model Training	Key: Turnkey solution
Physical	Dimensions (W x H x D)	482.6 mm (19″) x 175.2 mm (4U) x 1100 mm
	Weight	75 kg
	Material	Cold-rolled steel
	Drive Bays	8 x Hot-swappable 2.5″ NVMe U.2 Bays	Pre-configured in RAID 0 for maximum I/O
	GPU Configuration	4 x or 8 x NVIDIA A100/A800 80GB/40GB GPUs	Liquid-cooled, Full-height, Full-length
	Power Supply	4 x 3600W (Platinum Efficiency)	N+N Redundant
	Liquid Cooling	Direct-to-Chip on CPUs and GPUs	Closed-loop within chassis or ready for CDU
System Architecture	Processor	Dual Intel® Xeon® Platinum 8480+ or equivalent	High-core-count CPUs to feed GPUs
	Memory	1.5 TB DDR5 (48 x 32GB DIMMs)	Optimized for large dataset caching
	GPU Interconnect	NVIDIA NVLink™ Bridge across all GPUs	Key for high-speed GPU-to-GPU communication
	Network Controller	Dual-port 200G NDR InfiniBand or Ethernet	Mandatory for multi-node training scale-out
	BMC	Redfish-compliant
I/O & Connectivity	Front Panel	2 x USB 3.2, System Status LCD
	Rear Panel	2 x QSFP-DD (200G InfiniBand), 2 x USB, Management LAN
	Cooling Ports	2 x Coolant Inlet/Outlet (Quick-Disconnect)
Software & Management	Pre-installed Software	NVIDIA Base Command Manager, NGC Container Runtime, Driver Stack	Ready-to-run upon racking
	Supported Frameworks	Validated for PyTorch, TensorFlow, NVIDIA NeMo
	Orchestration	Integrated with NVIDIA DGX SuperPOD software stack	For cluster deployment
	Management	NVIDIA BMC extensions for GPU fleet management
Performance	AI Training Performance	> [e.g., 5] PetaFLOPS of FP16 (Tensor Core) performance	Benchmarked specific to configuration
	GPU Memory per Node	> 320 GB (With 4x 80GB GPUs)	Enables training of multi-billion parameter models
	NVMe Storage Bandwidth	> 20 GB/s aggregate read
Environmental	Operating Temperature (Coolant)	+15 °C to +45 °C (Coolant Inlet)
	Power Consumption (Max)	12,000W	Typical for 4x A100 liquid-cooled config
	Acoustic Noise	< 45 dBA
Certifications & Compliance	Safety	IEC/EN/UL 62368-1
	EMC	FCC Part 15 Class A, CE