QC

QCT QuantaGrid D75H-10U

rack
8× B300
One NVIDIA HGX B300 8-GPU baseboard; scale-out is eight ConnectX-8 OSFP ports carrying 800G Ethernet or InfiniBand at one port per GPU for GPU-Direct RDMA
FP8
PFLOPS
FP4
PFLOPS
Power
kW Total
Memory
2304
GB Total

QCT's 10U Blackwell Ultra server, built on the NVIDIA HGX B300 platform with two Intel Xeon 6 processors. Networking is eight ConnectX-8 OSFP ports at 800G, one per accelerator, for one-to-one GPU-Direct RDMA, and there is room for four full-height full-length PCIe Gen 5 slots. QCT quotes 72 PFLOPS of FP8 and 144 PFLOPS of FP4 without saying whether either is dense or sparse. Both match NVIDIA's sparse figures for this baseboard exactly, and neither matches the dense figures of 36 and 108, so they are recorded as sparse. Worth noting QCT calls the FP8 number a training figure, which would normally imply dense; the number itself settles the basis, not the label. Power is twelve 3,200 W supplies in N+N redundancy, which is capacity rather than draw, so no system power is shown.

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FP8
PFLOPS
FP4
PFLOPS

System Details

GPU Configuration

GPU Count: 8 GPUs
Architecture: Blackwell Ultra
Interconnect: One NVIDIA HGX B300 8-GPU baseboard; scale-out is eight ConnectX-8 OSFP ports carrying 800G Ethernet or InfiniBand at one port per GPU for GPU-Direct RDMA

System Specifications

Form Factor: rack
Total Power:
Total Memory: 2304 GB
Memory Bandwidth: 64000 GB/s

Precision Performance Breakdown

PrecisionSystem PerformancePer GPUEfficiency
— PFLOPS 0.0 TFLOPS
— PFLOPS 0.0 TFLOPS

All figures are dense. Vendors commonly headline the number, which is twice the dense one.

Powered by NVIDIA B300

This system utilizes 8 × NVIDIA B300 SXM 288GB GPUs, each delivering exceptional performance for AI and HPC workloads.

Per GPU TDP

1400W

Per GPU Memory

288 GB

Process Node

4nm

Architecture

Blackwell Ultra

Documentation & Resources

Official Datasheet

QCT QuantaGrid D75H-10U technical specifications

Download PDF

QCT QuantaGrid D75H-10U

QCT • Latest version

View Document ↗

Typical Use Cases

AI/ML Training
High-Performance Computing
Data Analytics

The QCT QuantaGrid D75H-10U runs 8× B300 GPUs over One NVIDIA HGX B300 8-GPU baseboard; scale-out is eight ConnectX-8 OSFP ports carrying 800G Ethernet or InfiniBand at one port per GPU for GPU-Direct RDMA.