NVIDIA DGX B300
- Condition
- New
- Manufacturer
- NVIDIA
- Supported CPU
- 2x Intel Xeon Platinum 6776P
- Supported RAM
- 32x 64GB DDR5-6400 (4TB)
- Power supply unit
- 12x 3000W
- HDD bays
- 2x 1.92TB NVMe SSD / 8x 3.84TB NVMe SSD
- GPU
- 8 x NVIDIA Blackwell Ultra SXM
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Submit a requestNVIDIA DGX B300 is an integrated accelerated computing system designed for enterprise artificial intelligence, machine learning, generative AI, AI reasoning, analytics, and high-performance computing (HPC) workloads. Built around eight NVIDIA B300 Blackwell Ultra Tensor Core GPUs, the platform provides a unified architecture for AI training, inference, and large-scale data processing in modern data centers.
Unlike a traditional GPU server assembled from individual components, NVIDIA DGX B300 combines GPU acceleration, high-speed interconnects, storage, networking, and a validated NVIDIA software stack in a single enterprise-ready platform. It can operate as a standalone AI compute node or serve as a building block for scalable DGX-based clusters.
GPU architecture for AI training and inference
NVIDIA DGX B300 is equipped with eight NVIDIA B300 Blackwell Ultra Tensor Core GPUs. The system provides 8 x 288 GB of GPU memory, or approximately 2.3 TB in total, giving enterprises the capacity required for reasoning models, large language models, generative AI applications, accelerated analytics, and HPC workloads.
The NVIDIA B300 Blackwell Ultra GPU is designed for demanding AI workloads, including large language model training, fine-tuning, inference, agentic AI, recommendation systems, computer vision, analytics, and scientific computing. Tensor Cores with support for advanced mixed-precision computing help accelerate neural network operations while maintaining the accuracy required for production workloads.
The eight GPUs are connected through fifth-generation NVIDIA NVLink and two fifth-generation NVIDIA NVLink switch systems, creating a high-bandwidth GPU communication fabric. This architecture provides 14.4 TB/s of aggregate NVLink bandwidth and allows multiple accelerators to efficiently operate together as a single computing domain for demanding distributed workloads.
The system is powered by two Intel Xeon Platinum 6776P processors with 64 cores each, providing 128 CPU cores in total. The factory configuration includes 2 TB of system memory and is upgradable to 4 TB, enabling efficient data preparation, containerized workloads, and CPU-side processing tasks required by AI pipelines.
Primary use cases
- AI model training and fine-tuning. DGX B300 accelerates development and optimization of large-scale AI models, including reasoning models, generative AI, natural language processing, computer vision, recommendation systems, and enterprise AI applications.
- Large-scale inference workloads. The platform is designed for deploying production AI services, intelligent applications, AI agents, automated decision systems, chatbots, and real-time model execution.
- Data analytics and accelerated computing. DGX B300 supports GPU-accelerated analytics, scientific computing, simulations, and workloads that combine traditional HPC methods with machine learning.
- Multi-user AI environments. NVIDIA Multi-Instance GPU (MIG) technology enables supported GPU partitioning into isolated instances with dedicated compute and memory resources, improving resource utilization for multiple teams and applications.
- Enterprise AI infrastructure. DGX B300 provides a standardized foundation for organizations building internal AI platforms, research environments, scalable machine learning operations, and private AI factory infrastructure.
NVIDIA DGX B300 in enterprise infrastructure
NVIDIA DGX B300 is designed for organizations that require dedicated AI computing resources for continuous development, testing, and production deployment. The platform enables data science teams, AI engineers, and enterprise developers to work within a consistent hardware and software environment instead of managing separate accelerator servers and integration layers.
The system can be deployed as an individual AI node or integrated into larger NVIDIA-based environments. When planning an enterprise deployment, organizations should evaluate not only GPU performance but also network architecture, external storage requirements, workload distribution, power availability, cooling capacity, and data center readiness.
With its integrated hardware design, NVIDIA software ecosystem, and support for scalable AI deployments, DGX B300 helps enterprises shorten the path from AI experimentation to production use. The platform provides a reliable foundation for organizations developing AI reasoning services, generative AI platforms, analytics solutions, and HPC applications that require predictable performance and simplified infrastructure management.
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