Turnkey AI Appliances
NVIDIA DGX appliances are the de facto standard for enterprise AI. Powered by eight NVIDIA SXM GPUs communicating via NVLink and NVSwitch, they provide the ultimate in compute performance and memory capacity for agentic AI, reasoning models and physical AI.
NVIDIA DGX is a whole lot more than a server, it's a turnkey solution, comprising compute node, AI-ready software stack and enterprise-level support.
As an NVIDIA Elite partner and the UK's only DGX Managed Service Provider, Scan can advise on the optimum configuration and install your DGX.
Enterprise AI Made Simple
NVIDIA AI Enterprise, included with DGX appliances, is an end-to-end software platform for building and deploying AI applications.
This collection of libraries, frameworks and NVIDIA Inference Microservices (NIMs) is specifically designed to reduce the complexity of building AI applications from scratch. Explore the range of optimised frameworks.
NVIDIA DGX Generations
Find out more about the features of the different generations of GPUs in DGX systems.
Rubin Architecture Features
DGX appliances with Rubin GPUs were announced in 2026 and are available to pre-order.
Built for agentic AI
Rubin features a specialised multi-agent engine for reasoning workflows, and a dedicated reinforcement learning engine that optimises memory movement in hardware.
Massive Memory Bandwidth
The DGX Rubin NVL8's eight GPUs are supported by 2.3TB of HBM4 memory with 176TB/s of bandwidth, a 1.8x increase over previous generation Blackwell systems.
NVIDIA NVLink
Sixth-generation NVLink provides 28.8TB/s of bandwidth between GPUs, double that of fifth-gen NVLink in previous generation Blackwell systems.
Blackwell Architecture Features
DGX appliances with Blackwell GPUs were announced in 2025 and are available now.
Built for AI factories
Blackwell introduced native support for FP4 precision, delivering up to 3x the training performance and 15x the inferencing speed of the previous generation Hopper architecture.
Dense NVFP4
There are two types of Blackwell GPUs. The Blackwell Ultra GPUs in the DGX B300 are specially optimised for low precision calculations, supporting several proprietary NVIDIA formats such as dense NVFP4, which can boost performance by up to 50% more than the standard Blackwell GPUs in the DGX B200.
NVIDIA NVLink
Fifth-generation NVLink provides 14.4TB/s of bandwidth between GPUs, double that of fourth-gen NVLink in previous generation Hopper systems.
NVIDIA DGX Platforms
Compare the specifications of the different DGX systems.
| Specification | DGX Rubin NVL8 | DGX B300 | DGX B200 |
|---|---|---|---|
| GPUs | 8x Rubin | 8x Blackwell Ultra | 8x Blackwell |
| Cooling | Liquid | Air | Air |
| GPU memory | 2.3TB HBM4 | 2.1TB HBM3e | 1.4TB HBM3e |
| GPU memory bandwidth | 176TB/s | 62TB/s | 64TB/s |
| NVLink | 6th gen | 5th gen | 5th gen |
| NVSwitch | 6th gen | 5th gen | 5th gen |
| NVLink bandwidth | 28.8TB/s | 14.4TB/s | 14.4TB/s |
| FP4 performance | 400 PFLOPS | 144 PFLOPS | 144 PFLOPS |
| CPUs | 2x Intel Xeon 6776P | 2x Intel Xeon 6776P | 2x Intel Xeon 8570 |
| System memory | TBC | 2TB or 4TB DDR5 | 2TB or 4TB DDR5 |
| Networking | 8x OSFP ports serving 8x single-port NVIDIA ConnectX-9 VPI – up to 800Gb/s NVIDIA InfiniBand and Ethernet 2x 400G QSP112 NVIDIA BlueField-4 DPUs – up to 800Gb/s NVIDIA InfiniBand and Ethernet |
8x OSFP ports serving 8x single-port NVIDIA ConnectX-8 VPI – up to 800Gb/s NVIDIA InfiniBand and Ethernet 2x dual-port QSP112 NVIDIA BlueField-3 DPUs – up to 400Gb/s NVIDIA InfiniBand and Ethernet |
8x OSFP ports serving 8x single-port NVIDIA ConnectX-7 VPI – up to 400Gb/s NVIDIA InfiniBand and Ethernet 2x dual-port QSP112 NVIDIA BlueField-3 DPUs – up to 400Gb/s NVIDIA InfiniBand and Ethernet |
| Storage | 2x 2TB OS SSDs 8x 4TB data SSDs |
2x 1.92TB OS SSDs 8x 3.84TB data SSDs |
2x 1.92TB OS SSDs 8x 3.84TB data SSDs |
| Software | NVIDIA DGX OS NVIDIA AI Enterprise NVIDIA Mission Control |
NVIDIA DGX OS NVIDIA AI Enterprise NVIDIA Mission Control |
NVIDIA DGX OS NVIDIA AI Enterprise NVIDIA Mission Control |
| Power usage | 24kW | 14.5kW (Busbar) 15.1kW (PSU) |
14.3kW |
| Form factor | 2U | 10U | 10U |
Discover how the different DGX appliances and other platforms compare in our AI training and inferencing hardware buyers guide.
Deploying your DGX
Scan is proud to be the UK's only NVIDIA DGX-Ready Managed Services Provider, offering in-country and global customer support. Our managed service portfolio offers a one-stop shop for DGX customers deploying, managing, and maintaining AI supercomputing infrastructure.
Recognising that many customers have teams with existing technical knowledge, we tailor our service offering to complement the existing expertise of your team.
We are also uniquely positioned to providing AI/machine learning development services to assist with optimising and accelerating the deployment of AI models.
Storage
The most demanding AI models such as generative, agentic and physical AI can only be trained efficiently with rapid access to huge datasets. AI-optimised storage appliances ensure that your DGX appliances are working at maximum efficiency.
We recommend software-defined storage appliances powered by PEAK:AIO, and further options from leading brands such as VAST Data, DDN, Hammerspace, Dell, NetApp and Weka.
Networking
Whether your project is starting with a single DGX or scaling up to a BasePOD (≤40 nodes) or a SuperPOD (≤140 nodes), it will require AI-optimised ultra-fast InfiniBand or Ethernet networking to connect the compute and storage nodes.
This ensures the DGXs are fully utilised at all times, and ROI is maximised across your entire AI infrastructure.
We can advise on the optimum configuration of NVIDIA Networking Smart NICs, Super NICs, DPUs, switches and interconnects.
Installation & Hosting
DGX appliances have much more demanding power and cooling requirements than conventional servers.
Our technical specialists will perform a site survey to see whether your facilities are suitable or can be adapted to host DGXs. This includes evaluating liquid cooling options, alongside differing power delivery methods, such as integrated PSUs versus busbars.
Alternatively, we can arrange installation at one of our NVIDIA-approved hosting partners.
Speak to an Expert
Discuss your DGX project requirements with Scan's specialist team.
Frequently Asked Questions
Find answers to common questions about NVIDIA DGX Rubin NVL8 and DGX B200 AI appliances.
The NVIDIA DGX Rubin NVL8 is a powerful AI supercomputer designed for agentic and physical AI at scale. It features eight NVIDIA Rubin GPUs, 2.3TB of HBM4 system memory, and 800GB/s high-speed networking. It includes the full NVIDIA AI software stack (additional charge may apply) and is the building block for the upcoming Vera Rubin NVL72 SuperPOD solutions.
The NVIDIA DGX Rubin NVL8 is expected to be available to purchase in the second half of 2026.
Register your interest here.
The next-generation Rubin platform includes the Rubin GPU (HBM4 memory), NVLink 6 Switch, ConnectX-9 SuperNIC, BlueField-4 DPU, and Spectrum-6 Ethernet / Quantum X800 InfiniBand switch. In contrast the current generation Blackwell includes the Blackwell and Blackwell Ultra GPUs (HBM3e memory), NVLink 5 Switch, ConnectX-8 SuperNIC, BlueField-3 DPU, and Spectrum-4 Ethernet / Quantum-2 InfiniBand switch.
Every aspect of the latest Rubin platform features an uplift in performance over the previous generation, resulting in significantly higher performance than Blackwell-based ones.
The DGX Rubin NVL8 is optimised for demanding AI workloads such as Agentic AI, Physical AI, large-scale Mixture-of-Experts (MoE) Models, Massive-Context Inference and next-generation AI factories.
Yes. Scan is an official UK NVIDIA Elite Partner and will be offering the DGX Rubin NVL8 with full configuration, deployment, and support services. Scan is the only UK-based DGX Managed Services Provider (MSP) that enables businesses to access the power of DGX infrastructure without needing the skillset on-site to oversee the infrastructure. Instead, DGX MSPs provide full wraparound services to assist with anything from the initial deployment & configuration through to on-going services that encompass support, updates and overall platform management.
The NVIDIA DGX B200 is a powerful AI supercomputer designed for enterprise and research use. It features 8 NVIDIA Blackwell GPUs, up to 4 TB of system memory, and high-speed networking, making it ideal for training and deploying large language models, generative AI, advanced inference, and scientific computing. It includes the full NVIDIA AI software stack (additional charge may apply) and is built for on-premise AI infrastructure as part of DGX BasePOD and SuperPOD solutions.
The DGX B200 is a next-generation upgrade over the DGX H100 & H200, offering major improvements in performance, memory, and AI model handling:
| Feature | H100 (Hopper) | H200 (Hopper Refresh) | B200 (Blackwell) |
|---|---|---|---|
| GPU Architecture | Hopper | Hopper (with HBM3e) | Blackwell |
| Launch Year | 2022 | 2024 | 2024 (announced), shipping 2H 2024 |
| FP8 Training Perf. | ~32 petaFLOPS (DGX H100) | Same as H100 | ~72 petaFLOPS (DGX B200) |
| FP4 Inference Perf. | N/A | N/A | ~144 petaFLOPS (DGX B200) |
| Memory Capacity | 80 GB HBM3 | 141 GB HBM3e | 192 GB HBM3e |
| Memory Bandwidth | 3.35 TB/s | 4.8 TB/s | ~6 TB/s |
| Transformer Engine | 1st-gen | 1st-gen | 2nd-gen with FP4/FP8 support |
| NVLink Support | Yes (NVLink 4) | Yes | Yes (faster, 1.8 TB/s via NVSwitch) |
| Target Use Case | AI training, HPC | Bigger models, more memory-bound | Massive LLMs, GenAI, real-time inference |
Summary
- H100: Great for general AI training and HPC, computer vision NLP and deep learning. Offers an excellent balance between compute power and memory for most AI workloads.
- H200: Boosted memory version of H100; ideal for larger, memory-bound models like LLMs, memory-intensive AI inference and foundational model tuning.
- B200: The next-gen flagship; ideal for training and deploying large-scale LLMs, generative AI at scale and multi-GPU systems.
The DGX B200 is optimised for demanding AI workloads such as large-scale deep learning training, generative AI (including LLMs and diffusion models), high-performance inference, data analytics, and scientific computing. With its 8 Blackwell GPUs, ultra-fast memory, and high-speed networking, it's especially well-suited for enterprises and research institutions developing foundation models, deploying real-time AI applications, or running complex simulations.
Yes. Scan is an official UK NVIDIA Elite Partner offering the DGX B200 with full configuration, deployment, and support services. Scan is a DGX MSP (Managed Services Provider) that enables businesses to access the power of DGX infrastructure, like the DGX B200, without needing the skillset on-site to oversee the infrastructure. Instead, DGX MSPs provide full wraparound services to assist with anything from the initial deployment & configuration through to on-going services that encompass support, updates and overall platform management.
The NVIDIA DGX B200 is a high-performance AI system featuring 8× NVIDIA Blackwell B200 GPUs with 1,440 GB of HBM3e memory, delivering up to 72 petaFLOPS of AI training performance. It includes dual Intel Xeon Platinum CPUs, up to 2 TB of system RAM (expandable to 4 TB), and a mix of NVMe SSD storage for OS and data caching. The system supports high-speed networking with up to 400 Gb/s InfiniBand or Ethernet and comes with advanced software tools including NVIDIA AI Enterprise and Base Command. It fits into a 10U rack space and consumes up to 14.3 kW of power.
Scan provides full deployment services, including consultation, infrastructure assessment, rack integration, and ongoing support, tailored for enterprise and research environments.
Yes, the DGX B200 is purpose-built for on-premise AI infrastructure. It delivers powerful performance for training, inference, and analytics with 8 Blackwell GPUs, high-bandwidth NVSwitch interconnects, and up to 4 TB of system memory. Its 10U rackmount form factor, enterprise-grade networking (up to 400 Gb/s), and support for NVIDIA AI Enterprise software make it ideal for datacenters and organisations deploying advanced AI workloads on-site. However, if you can't host this internally, we have several data centre partnerships in place to assist with co-location services as part of a complete services contract with Scan.
The DGX B200 is ideal for CTOs, AI infrastructure leads, data centre architects, and researchers in enterprise, healthcare, academia, and government sectors needing cutting-edge performance for training and deploying AI models.
The Blackwell GPU architecture is designed specifically for next-generation AI workloads, offering major advances in performance, efficiency, and scalability. Key features include:
- Transformational AI performance: Supports FP4 and FP8 formats for massive throughput, ideal for training and inference of large language models and generative AI.
- Second-gen Transformer Engine: Accelerates training and inference of transformer-based models more efficiently than previous architectures.
- Enhanced NVLink bandwidth: Enables faster GPU-to-GPU communication for multi-GPU systems like the DGX B200.
- Advanced memory architecture: Uses high-capacity HBM3e memory for up to 1.5 TB/s bandwidth per GPU.
- Security and reliability: Includes confidential computing and RAS (reliability, availability, and serviceability) features to support enterprise and mission-critical environments.
These innovations make Blackwell GPUs particularly well-suited for ultra-large-scale AI models, delivering breakthrough performance in both compute and energy efficiency.
Yes. Scan can assess your current infrastructure and deliver a fully compatible DGX B200 deployment plan, including cooling, networking, and power considerations.
Absolutely. The DGX B200 is built for scalable AI infrastructure and can be clustered into DGX BasePODs or DGX SuperPODs. By interconnecting multiple DGX B200 systems using NVIDIA Quantum-2 InfiniBand or Ethernet with ConnectX-7 and BlueField-3, organisations can build AI datacenters capable of training and deploying the largest generative AI models and LLMs. These clusters benefit from the DGX B200's ultra-fast NVLink and NVSwitch architecture for multi-node GPU communication, ensuring minimal bottlenecks at scale.
The DGX B200 is purpose-built to accelerate generative AI and LLM workloads at scale. It features 8 Blackwell GPUs with a combined 1,440 GB of HBM3e memory and up to 72 petaFLOPS of AI training performance, enabling it to train and fine-tune massive models efficiently. The system's second-gen Transformer Engine, high-bandwidth NVSwitch interconnects, and support for FP4/FP8 precision allow for faster training and inference of transformer-based architectures. Integrated with the NVIDIA AI software stack, the DGX B200 offers a complete platform for developing, deploying, and managing LLMs and generative AI applications both on-premise and in hybrid environments.
The NVIDIA DGX B200 is equipped with advanced networking features designed to meet the demands of high-performance AI workloads:
- High-Speed Connectivity: It includes 4 OSFP ports accommodating 8 single-port NVIDIA ConnectX-7 VPI adapters, each supporting up to 400 Gb/s for both InfiniBand and Ethernet connections.
- Data Processing Units (DPUs): The system features 2 dual-port QSFP112 NVIDIA BlueField-3 DPUs, each capable of up to 400 Gb/s, facilitating efficient data handling and network offloading.
- Management Networking: For system management, it provides a 10 Gb/s onboard NIC with RJ45, a 100 Gb/s dual-port Ethernet NIC, and a host baseboard management controller (BMC) with RJ45.
These networking capabilities ensure that the DGX B200 can handle intensive data transfer requirements, making it suitable for scalable AI deployments and integration into high-performance computing environments.
As pricing depends on configuration and support options, contact Scan's enterprise team for a tailored quote and expert consultation.