The NVIDIA HGX B300 represents the latest in NVIDIA’s GPU server architecture designed for high-performance computing (HPC), AI model training, and large-scale inference. As a reference platform, it provides a standardized building block for GPU-dense servers, enabling enterprises and data centers to deploy compute-intensive workloads efficiently.
Overview of NVIDIA HGX B300
HGX B300 is NVIDIA’s 8-GPU reference platform built for Blackwell Ultra GPUs, supporting workloads that demand high compute density, massive GPU memory, and low-latency GPU-to-GPU communication. Key features include:
- GPU Configuration: 8 × NVIDIA Blackwell Ultra SXM GPUs with FP4 Tensor cores.
- Memory Capacity: Up to 2.1 TB of GPU memory per node, optimized for large models.
- Interconnect Bandwidth: NVLink/NVSwitch fabric offering 1.8 TB/s per GPU and a total interconnect bandwidth of 14.4 TB/s.
- Networking: Supports high-speed networking, including 800 Gbps InfiniBand or Spectrum-X Ethernet, suitable for multi-node scaling.
- Target Workloads: AI training (LLMs, generative AI), inference at scale, HPC simulations, and deep learning research.
The HGX B300 architecture enables vendors to build servers that standardize GPU performance and connectivity, simplifying deployment and scaling in data center environments.
Implementation in Servers
Saitech offers a variety of servers equipped with HGX B300, sourced from leading OEMs such as ASRock, GIGABYTE, Supermicro, and ASUS. These implementations leverage the B300 architecture to deliver high compute density and flexibility. Below are notable examples:
Supermicro AS-8126GS-NB3RT
- Form Factor: 8U
- CPU: Dual AMD EPYC 9004 series processors
- GPU Configuration: 8 × NVIDIA Blackwell Ultra GPUs (via HGX B300 NVSwitch)
- Memory: Supports up to 6 TB DDR5
- Networking: Up to 100 Gbps Ethernet, InfiniBand options
- Use Case: Large-scale AI model training, HPC simulations, and GPU-dense data center deployments
ASUS XA NB3I-E12
- Form Factor: 9U
- CPU: Dual Intel 6th Gen Xeon Scalable
- GPU Configuration: 8 × NVIDIA Blackwell Ultra GPUs via HGX B300
- Memory: 3 TB DDR5
- Expansion: Multiple NVMe drives, PCIe 5.0 slots
- Use Case: Enterprise AI workloads, HPC research, and generative AI training
GIGABYTE G894-ZD3-AAX7
- Form Factor: 8U
- CPU: Dual AMD EPYC processors
- GPU Configuration: 8 × NVIDIA Blackwell Ultra GPUs with NVSwitch
- Memory: Up to 4 TB DDR5
- Networking: 200/400 Gbps InfiniBand options
- Use Case: High-performance AI model training, large-scale inference, and HPC workloads
ASRock 8U16X-GNR2
- Form Factor: 8U
- CPU: Dual Intel Xeon processors
- GPU Configuration: 8 × NVIDIA Blackwell Ultra GPUs (HGX B300)
- Memory: DDR5, up to 4 TB
- Use Case: AI and HPC compute clusters, research workloads, and enterprise-scale GPU deployments
These servers implement HGX B300 to deliver high GPU density with optimized interconnects, allowing enterprises to scale AI and HPC workloads without compromising on throughput or latency.
Typical Workloads and Use Cases
HGX B300 servers are particularly suited for:
- Large-scale AI model training: Including large language models (LLMs) and generative AI applications.
- AI inference at scale: High-throughput, low-latency inference in multi-tenant or enterprise environments.
- HPC simulations: Scientific modeling, weather simulations, and complex computational tasks.
- Data center AI deployments: Rack-scale clustering of HGX B300 nodes for AI “factories,” enabling scalable and standardized compute architecture.
The combination of high GPU memory, NVLink/NVSwitch interconnect, and multi-node networking allows these servers to handle modern AI workloads efficiently, making them indispensable for enterprises investing in AI and HPC infrastructure.
Conclusion
As an authorized reseller of NVIDIA and leading server brands, Saitech provides access to a wide range of HGX B300-based servers from vendors such as ASRock, GIGABYTE, Supermicro, and ASUS. These servers provide enterprise-grade performance and scalability, ensuring businesses can meet the growing demands of AI, HPC, and data-intensive workloads.
HGX B300’s standardized architecture, high compute density, and modular design make it a key component for modern GPU clusters, enabling organizations to deploy, scale, and maintain AI and HPC workloads with confidence.
