NVIDIA GH200 Grace Hopper Superchip 96GB HBM3 699-2G530-0215-DV5
$3,599.96
NVIDIA GH200 Grace Hopper Superchip 96GB HBM3 699-2G530-0215-DV5 — 96GB HBM3 GPU memory plus Grace CPU LPDDR5X platform memory Grace Hopper CPU+GPU superchip / development module for generative AI, large language models, HPC, scientific computing, memory-intensive accelerated workloads and Grace Hopper software development. Review specifications and compatibility, then contact AI Robot Supplier to confirm exact stock, configuration and lead time.
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NVIDIA GH200 Grace Hopper Superchip 96GB HBM3 699-2G530-0215-DV5 Overview
NVIDIA GH200 Grace Hopper Superchip 96GB HBM3 699-2G530-0215-DV5 is a Grace Hopper CPU+GPU superchip / development module based on NVIDIA’s Grace + Hopper platform. It is designed for generative AI, large language models, HPC, scientific computing, memory-intensive accelerated workloads and Grace Hopper software development. With 96GB HBM3 GPU memory plus Grace CPU LPDDR5X platform memory, this product targets organizations that need substantially more accelerator capability than a conventional consumer GPU can provide.
Buyers comparing the GH200 96GB price should evaluate more than memory capacity or headline performance. Server compatibility, cooling design, power delivery, software support, physical form factor, board revision, workload precision and deployment topology can determine whether an accelerator is suitable for a specific system. AI Robot Supplier recommends confirming the intended host platform and exact required configuration before completing a high-value order.
The NVIDIA GH200 Grace Hopper is positioned for professional and enterprise use. Typical buyers include AI companies, research laboratories, universities, cloud operators, engineering teams, system integrators and organizations building private AI infrastructure. This product page is structured to help procurement teams compare key specifications, compatibility requirements and deployment considerations before requesting final stock confirmation.
Key Features of NVIDIA GH200 Grace Hopper Superchip 96GB HBM3 699-2G530-0215-DV5
- Enterprise accelerator class: built for sustained professional and data-center workloads rather than ordinary gaming use.
- High-capacity memory: 96GB HBM3 GPU memory plus Grace CPU LPDDR5X platform memory, supporting demanding AI, visualization or HPC workloads appropriate to this model.
- Grace + Hopper architecture: NVIDIA platform technologies designed for accelerated computing.
- Professional deployment: designed for compatible server, workstation or development platforms rather than arbitrary desktop installation.
- AI and compute workflows: applicable to generative AI, large language models, HPC, scientific computing, memory-intensive accelerated workloads and Grace Hopper software development.
- Pre-order configuration check: buyers can confirm compatibility, quantity, destination and lead time before payment.
For teams building AI infrastructure, the value of NVIDIA GH200 Grace Hopper Superchip 96GB HBM3 699-2G530-0215-DV5 is determined by the complete system around it. CPU choice, PCIe topology, memory, storage, networking, thermal design and software versions can materially affect real-world throughput. For multi-GPU deployments, confirm server validation, slot spacing, NUMA topology, interconnect requirements and available power before procurement.
NVIDIA GH200 Grace Hopper Superchip 96GB HBM3 699-2G530-0215-DV5 Applications
The NVIDIA GH200 Grace Hopper Superchip 96GB HBM3 699-2G530-0215-DV5 is suitable for organizations evaluating accelerated infrastructure for generative AI, large language models, HPC, scientific computing, memory-intensive accelerated workloads and Grace Hopper software development. Depending on the exact software stack and configuration, potential use cases include large-model development, AI inference services, accelerated research, simulation, rendering, virtualized GPU environments and specialized professional computing.
Artificial Intelligence and Machine Learning
AI workloads can demand large amounts of accelerator memory and high data throughput. The NVIDIA GH200 Grace Hopper Superchip 96GB HBM3 699-2G530-0215-DV5 may be used for supported model training, fine-tuning, inference and enterprise AI services. Actual model capacity and throughput depend on numerical precision, framework versions, batch size, quantization, host memory, storage and whether the workload scales efficiently across the chosen platform.
High-Performance and Scientific Computing
GPU acceleration can reduce execution time for suitable simulation, analytics and scientific workloads. Organizations should validate application support for the NVIDIA software ecosystem used by the target accelerator and confirm that the host platform meets the workload’s CPU, memory, networking and storage requirements.
Enterprise Infrastructure
For private AI clouds and enterprise GPU servers, procurement should include a complete capacity plan. This includes expected concurrent users, memory requirements, model sizes, inference latency targets, power budget, cooling capacity and network fabric. Selecting the correct GPU is only one part of building a reliable production system.
NVIDIA GH200 Grace Hopper Superchip 96GB HBM3 699-2G530-0215-DV5 Specifications
| Manufacturer | NVIDIA |
|---|---|
| Product | NVIDIA GH200 Grace Hopper Superchip 96GB HBM3 699-2G530-0215-DV5 |
| Architecture | Grace + Hopper |
| Memory | 96GB HBM3 GPU memory plus Grace CPU LPDDR5X platform memory |
| Product Class | Grace Hopper CPU+GPU superchip / development module |
| CPU | 72 Arm Neoverse V2 cores |
| GPU Architecture | NVIDIA Hopper |
| GPU Memory | 96GB HBM3 on this referenced configuration |
| CPU Memory | Grace platform supports up to 480GB LPDDR5X |
| GPU Memory Bandwidth | up to 4 TB/s for 96GB HBM3 configuration |
| CPU-GPU Interconnect | NVLink-C2C, up to 900 GB/s coherent interface |
| Compute Model | CPU+GPU coherent memory architecture |
| Part Number | 699-2G530-0215-DV5 |
| Availability | Contact AI Robot Supplier to confirm current stock, exact board configuration and lead time before ordering. |
Specification note: enterprise accelerator specifications can vary by board revision, OEM part number, firmware or configured platform. The exact supplied part number should be confirmed for system-level compatibility. Manufacturer documentation should take priority if a configuration-specific value differs.
NVIDIA GH200 Grace Hopper Superchip 96GB HBM3 699-2G530-0215-DV5 Compatibility and Deployment
GH200-compatible development/server platforms; this is not a conventional desktop PCIe graphics card and deployment must match the exact PG530/board configuration. Before purchase, verify the motherboard or accelerator baseboard, physical clearance, power connectors, PSU capacity, cooling, firmware, operating system, NVIDIA driver branch and application support.
Passive data-center accelerators depend on chassis airflow and should not be installed in an enclosure that cannot maintain the manufacturer’s thermal requirements. Similarly, module-style accelerators and superchips cannot be treated as standard add-in graphics cards. If you are replacing hardware in an existing server, provide the server manufacturer, model and current GPU configuration so compatibility can be reviewed before shipment.
For cluster deployments, also confirm network requirements such as Ethernet or InfiniBand, storage throughput and orchestration software. Production AI infrastructure should be designed around the workload rather than choosing the accelerator in isolation.
NVIDIA GH200 Grace Hopper Superchip 96GB HBM3 699-2G530-0215-DV5 Price and Ordering
The listed regular price on this product page is the current AI Robot Supplier selling price for this SKU/configuration. Enterprise GPU inventory can change quickly, so customers ordering multiple units should request a formal quotation or proforma invoice with the destination country, required quantity and desired delivery schedule.
Before payment, request confirmation of the exact product revision, condition, included accessories, packaging, warranty route and lead time applicable to your order. Shipping, customs duties, taxes and optional integration services may vary by destination.
For related accelerator options, browse Graphics Cards and Networking & AI Infrastructure.
Manufacturer reference: NVIDIA product/documentation resource.
NVIDIA GH200 Grace Hopper Superchip 96GB HBM3 699-2G530-0215-DV5 FAQ
What is the NVIDIA GH200 Grace Hopper Superchip 96GB HBM3 699-2G530-0215-DV5 designed for?
It is designed for generative AI, large language models, HPC, scientific computing, memory-intensive accelerated workloads and Grace Hopper software development. The exact workload fit depends on software support, model size, precision, host platform and system architecture.
How much memory does the NVIDIA GH200 Grace Hopper Superchip 96GB HBM3 699-2G530-0215-DV5 have?
This listing is for the configuration described as 96GB HBM3 GPU memory plus Grace CPU LPDDR5X platform memory. Confirm the exact part number before deployment because similarly named NVIDIA products can exist in different memory or platform configurations.
Can the NVIDIA GH200 Grace Hopper Superchip 96GB HBM3 699-2G530-0215-DV5 be installed in any PC?
No. Enterprise GPUs and accelerator modules have specific requirements for form factor, power, cooling, firmware and supported host platforms. Some products require purpose-built servers and cannot operate as standard consumer graphics cards.
Does AI Robot Supplier support quantity orders?
Yes. For multiple units, provide the quantity and delivery country so current stock, lead time, shipping method and a formal commercial quotation can be confirmed.
Is the listed price guaranteed for future orders?
The page displays the current regular selling price, but high-end accelerator inventory and international supply conditions can change. Confirm the price and availability when requesting a quotation for a specific order.
What should I provide for a compatibility check?
Send the server or workstation manufacturer and model, motherboard or baseboard information, existing accelerator configuration, power supply details and intended workload. For clusters, include the expected number of GPUs and networking requirements.
Where can I compare other AI GPUs?
You can browse AI Robot Supplier’s Graphics Cards and Networking & AI Infrastructure categories for other NVIDIA, AMD and Intel accelerators suitable for AI, HPC and professional compute workloads.
