SAN JOSE and ST. LOUIS, CA, Nov 18, 2025 – Super Micro Computer has introduced turnkey solutions that streamline deployment and reduce setup time for AI factories. The rack-scale clusters use NVIDIA Enterprise Reference Architectures and Blackwell GPUs and are integrated and validated by Supermicro. Each system ships as a full-stack package with the NVIDIA software stack and NVIDIA Spectrum-X ethernet networking. Supermicro’s DCBBS supports new data-center builds and data-center conversions by supplying the hardware and software needed to create an AI factory while reducing lead times and minimizing dependence on vendors.
“Supermicro has always led the industry in time-to-market for new GPU technologies at rack-scale, and we’re leveraging our expertise in delivering large-scale NVIDIA GB300 NVL72 and NVIDIA HGX B300-based AI infrastructure to enable the democratization of AI for enterprises in every industry,” said Charles Liang, president and CEO of Supermicro. “The AI factory is the foundation for transforming every company into an AI company, and in combination with our Data Center Building Block Solutions, Supermicro and NVIDIA are helping enterprises accelerate and streamline the deployment of AI factories for the industry’s shortest time-to-online (TTO).”
Supermicro offers AI factory solutions based on Supermicro NVIDIA-certified systems featuring NVIDIA Blackwell GPUs. Supermicro AI Factory solutions include Spectrum-X networking and are based on the NVIDIA Enterprise Reference Architectures for NVIDIA RTX PRO 6000 Blackwell server edition GPUs and NVIDIA HGX B200.
Supermicro AI factory cluster solutions are available from 4 nodes and 32 GPUs up to 32 nodes and 256 GPUs. The clusters are tested up to L12 (multi-rack cluster) at Supermicro’s production sites, and include the NVIDIA software stack (NVIDIA AI Enterprise, NVIDIA Omniverse, NVIDIA Run:ai), NVIDIA Spectrum-X ethernet networking, and integrated cabling for a solution that is plug-and-play and ready to start generating tokens from day one. Supermicro offers storage solutions for each stage of the AI data pipeline, using its portfolio of storage-optimized platforms. Working with data-management software partners, Supermicro supports the NVIDIA AI data platform reference design and enables AI workflows within the AI factory.
Supermicro is taking orders for AI factory cluster solutions in 4, 8, and 32-node configurations with NVIDIA RTX PRO 6000 Blackwell server edition or NVIDIA HGX B200 GPUs, optimized for AI and HPC workloads.
Universal AI, HPC, and visual computing clusters with NVIDIA RTX PRO 6000 Blackwell server edition GPUs – Based on Supermicro’s 4U and 5U PCIe GPU systems, with 8 GPUs per node in a 2-8-5-200 (CPU-GPU-NIC-Bandwidth) configuration, these cluster solutions can handle AI inference, enterprise HPC, and graphics & rendering workloads, enabling enterprises to leverage infrastructure for multiple applications.
High performance AI and HPC clusters with NVIDIA HGX GPUs – Based on Supermicro’s 10U modular GPU platforms, each node includes NVIDIA HGX B200 8-GPU and supports NVIDIA NVLink for GPU-GPU communication. These clusters are optimized for AI model fine-tuning and training, as well as HPC workloads.
Source: Supermicro
About Super Micro Computer
Super Micro Computer Inc., or Supermicro, is a provider of high-performance server technology and green computing solutions. Founded in 1993 by Charles Liang and Sara Liu, the company is headquartered in San Jose, CA. Supermicro offers a complete range of products, including servers, storage systems, networking devices, and server management software, serving industries like enterprise data centers, cloud computing, artificial intelligence, 5G, and edge computing. As of June 2023, the company employs approximately 5,126 individuals globally.
About NVIDIA
NVIDIA, founded in 1993 and headquartered in Santa Clara, CA, designs and manufactures graphics processing units, systems on chips, networking hardware, and AI intelligence software such as CUDA. Its products serve industries including gaming, data centers, autonomous vehicles, professional visualization, robotics, health care, and energy. The company introduced the GPU in 1999 and later expanded into accelerated computing and AI infrastructure. In gaming, its GPUs support high-performance rendering, while in AI and high-performance computing, its systems provide the infrastructure for training and deploying large-scale models. NVIDIA also develops tools for robotics and autonomous driving.