In modern AI training, high throughput compute tasks and high performance computing environments, systems must supply dense GPU capability together with strong CPU support. The Supermicro NVIDIA SRS-GB300-NVL72 offers a full rack structure that combines 72 Blackwell GPUs with 36 Grace CPUs. This design supports training clusters, research labs, and large data pipelines with steady performance and predictable scaling.
This rack brings together compute, cooling, power and networking inside a single structure. It removes many traditional limits found in node based setups and supports a wider range of training and inference tasks. Large model work, multi step processing and memory intensive operations gain strong support because the entire rack is built for unified GPU communication.
Core Features of Supermicro NVIDIA SRS-GB300-NVL72
Processor and Architecture
Each rack contains 36 Grace processors. These processors support the GPUs by handling scheduling, data movement, and task control. The GB300 structure links every compute zone in a direct pattern that helps handle demanding AI workloads without delay.
GPU and Acceleration
The rack supplies 72B three hundred GPUs. These GPUs are connected through a complete NVLink fabric that allows each GPU to share data directly with every other GPU. This removes many limits found in standard distributed setups. The combined HBM3 memory reaches nearly 21 terabytes, suited for very large models, simulation tasks or workloads with wide context windows.
Memory and Storage
System memory reaches up to seventeen terabytes of LPDDR5 X. This capacity assists CPU tasks that prepare data for GPU operations. Storage support includes up to one hundred 44 E one S PCIe5 drives, which offer fast access for datasets, checkpoints, or high-volume training material.
Networking and IO
The system includes ConnectX8 SuperNICs that supply strong fabric performance for cluster communication. This structure supports both InfiniBand and Spectrum X Ethernet, allowing the rack to link with larger clusters or act as a main compute block for a training environment.
Cooling and Power
Direct liquid cooling manages heat across all compute zones. The rack contains eight power shelves that together deliver a total output close to one hundred 32 kilowatts. The cooling distribution unit includes redundant pumps and power sources, helping maintain steady operation during long workloads.
Performance and Use Cases
This rack is well-suited for very large model training, complex multi layer inference and scientific computing. It supports research teams, enterprise data groups and dedicated AI facilities that require steady GPU throughput at scale. The integrated design helps remove bottlenecks across compute, memory and networking.
Why Choose This Rack
The system provides high density GPU compute in a unified structure. It offers strong cooling, large memory support and consistent GPU communication. The integrated networking fabric and storage capacity allow the rack to support a wide range of data-heavy workloads.
Availability at Saitech
Saitech offers this full rack system with configuration assistance and guidance for part selection. Their team supports memory planning, storage layout, and GPU quantity choices based on project needs. Buyers can request build notes, compatibility checks and shipment handling suited for data centers and research facilities. The Supermicro NVIDIA GB300 NVL72 is listed with clear technical information, allowing you to choose a setup that matches your training goals or large data tasks. Saitech also assists with order coordination, which helps ensure that the system arrives ready for installation and integration.
