NVIDIA HGX Systems
Power your AI factories with NVIDIA Blackwell architecture. From GPU clusters to complete rack-scale solutions, we deliver unprecedented computational performance, density, and efficiency.
Unprecedented AI Performance
Unprecedented Performance
Up to 15x inference and 3x training performance over previous generation
Maximum Density
Up to 144 GPUs in a single rack for hyperscale AI deployments
Advanced Cooling
Direct liquid cooling captures up to 98% of heat for 40% power savings
High-Speed Networking
800Gb/s compute fabric with integrated SuperNICs
NVIDIA Blackwell Architecture Solutions
A comprehensive range of air-cooled and liquid-cooled systems optimized for NVIDIA HGX platforms.
HGX B300 8-GPU System
4U Liquid-Cooled or 8U Air-Cooled
High-performance 8-GPU system featuring NVIDIA Blackwell Ultra architecture with integrated networking for turnkey deployment.
GPUs per Rack
Up to 64 (liquid-cooled)
GPU-GPU Interconnect
1.8TB/s
HBM3e Memory
288 GB per GPU
Networking
800Gb/s Compute Fabric
Key Features:
HGX B200 8-GPU System
8U/10U Air-Cooled or 4U Liquid-Cooled
Next-generation air-cooled and liquid-cooled systems with enhanced cooling architecture and high configurability.
GPUs per Rack
Up to 96 (liquid-cooled)
GPU-GPU Interconnect
1.8TB/s
HBM3e Memory
180 GB per GPU
Power Savings
Up to 40% with DLC
Key Features:
GB300 NVL72 Rack System
72 GPU Liquid-Cooled Rack
Exascale supercomputer in a single rack combining 72 NVIDIA Blackwell Ultra GPUs with Grace CPUs for ultimate AI performance.
Total GPUs
72 Blackwell Ultra
Total CPUs
36 Grace CPUs
NVLink Domain
All 72 GPUs connected
CDU Capacity
250kW liquid-to-liquid
Key Features:
2-OU Liquid-Cooled System
HGX B300 Ultra-Dense
Unmatched GPU density for hyperscale deployments with up to 144 GPUs per rack in compact 2-OU nodes.
GPUs per Rack
Up to 144
Nodes per Rack
Up to 18
HBM3e Memory
288 GB per GPU
Rack Standard
21-inch OCP ORV3
Key Features:
Air-Cooled & Liquid-Cooled Options
Choose the cooling solution that best fits your data center requirements and workload demands.
Air-Cooled Systems
Enhanced cooling architecture with next-gen heatsinks for standard data center deployment.
- Up to 32 GPUs per rack
- Front or rear I/O options
- Standard data center compatible
- Enhanced serviceability
Liquid-Cooled Systems
Direct liquid cooling technology for maximum density and efficiency.
- Up to 144 GPUs per rack
- Up to 98% heat capture
- 40% power savings
- Noise levels as low as 50dB
Powering AI Workloads
Large Language Model Training
Train foundation models and LLMs at scale with massive GPU clusters
AI Inference at Scale
High-throughput inference for production AI applications
Scientific Computing
Complex simulations, climate modeling, and research workloads
Generative AI
Power generative AI applications with unprecedented compute
AI Agent Factories on HGX
Train, fine-tune and serve enterprise-grade agent populations on the same rack. HGX delivers the memory, NVLink fabric and throughput required to operate thousands of concurrent agent sessions with predictable latency.
Train Your Own Agents
Fine-tune Llama, Mistral or Nemotron on your domain data, RLHF for agent behaviour and tool-use, distill into faster student models.
High-Throughput Inference
NIM microservices on HGX serve thousands of concurrent agent token streams with sub-second TTFT, backed by NVLink + 800Gb/s networking.
Population-Scale Memory
288 GB HBM3e per GPU and 1.8 TB/s GPU-GPU bandwidth keep large agent populations resident with their tools, RAG indexes and KV caches.
Multi-Tenant Governance
Run isolated agent fleets per business unit on shared infrastructure, with NeMo Guardrails, audit logging and policy enforcement at the cluster level.
A unified path from pilot to production fleet
Prototype on a GPU workstation, pilot on a DGX Spark, then promote the same agent stack to an HGX cluster for company-wide rollout. Same containers, same code, same governance model.
Ready to Build Your AI Infrastructure?
Contact us to discuss your requirements and get a customized NVIDIA HGX solution for your AI workloads.
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