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NVIDIA Grace Blackwell systems
GB200 and GB300 are bought as racks, not as cards. This page separates the two platforms cleanly, keeps NVIDIA's sparsity basis attached to every number, and works through what the rack asks of the building.
What are NVIDIA Grace Blackwell systems?
NVIDIA Grace Blackwell systems combine NVIDIA Grace CPUs and Blackwell GPUs in tightly integrated AI platforms. The correct choice depends on the exact platform generation, rack or server configuration, workload, memory and interconnect requirements, site power and cooling capacity, software stack, and verified commercial availability.
Why the CPU is part of the accelerator decision
In a conventional GPU server, CPUs and accelerators are separate subsystems joined over PCIe. Grace Blackwell integrates an Arm-based NVIDIA Grace CPU with Blackwell GPUs over a coherent link, and then joins many of those units into a single NVLink domain across the rack.
The practical consequence is that the scale-up domain becomes much larger than one server. A job that needs many accelerators to behave as one tightly coupled unit sees a rack rather than a node. That is the reason to consider the platform, and it is also the reason the rack becomes a facility project.
GB200 Grace Blackwell Superchip
NVIDIA publishes 1 Grace CPU with 2 Blackwell GPUs, 372 GB HBM3E at 16 TB/s, 3.6 TB/s of NVLink bandwidth, 72 Arm Neoverse V2 cores, and up to 480 GB of LPDDR5X CPU memory.
NVL72 rack-scale systems
72 GPUs and 36 Grace CPUs joined in one NVLink domain with 130 TB/s of NVLink bandwidth, published by NVIDIA for both GB200 NVL72 and GB300 NVL72.
NVL4 and OEM variants
Manufacturers publish smaller Grace Blackwell configurations as well. Dell publishes PowerEdge XE8712 as a GB200 NVL4 system with 4 NVIDIA B200 GPUs and 2 Grace processors in a 1OU form factor.
GB200 NVL72 and GB300 NVL72
These are two different platforms with two different memory profiles, and NVIDIA publishes their compute figures on different sparsity bases. The table keeps each on its own published basis rather than normalizing them into a single column.
| Specification | GB200 NVL72 | GB300 NVL72 |
|---|---|---|
| Configuration | 36 Grace CPUs, 72 Blackwell GPUs | 36 Grace CPUs, 72 Blackwell Ultra GPUs |
| GPU memory and bandwidth | 13.4 TB HBM3E, 576 TB/s | 20 TB, up to 576 TB/s |
| Fast memory | Not published as a separate figure | 37 TB |
| CPU memory and bandwidth | 17 TB LPDDR5X, 14 TB/s | 17 TB LPDDR5X, 14 TB/s |
| CPU cores | 2,592 Arm Neoverse V2 cores | 2,592 Arm Neoverse V2 cores |
| NVLink bandwidth | 130 TB/s | 130 TB/s |
| FP4 Tensor Core | 1,440 PFLOPS sparse, 720 PFLOPS dense | 1,440 PFLOPS with sparsity, 1,080 PFLOPS without sparsity |
| FP8 or FP6 Tensor Core | 720 PFLOPS sparse | 720 PFLOPS with sparsity |
| FP16 or BF16 Tensor Core | 360 PFLOPS sparse | 360 PFLOPS with sparsity |
| Cooling | Confirm with the specific configuration | NVIDIA describes a fully liquid-cooled rack-scale architecture |
SLYD does not publish a generational performance multiplier for these platforms. NVIDIA's own comparative claims come with workload, precision, software, and configuration context, and that context does not survive being compressed into a single number.
Which platform fits the requirement
When memory capacity is the binding constraint
Long-context inference, very large models, and workloads where the working set does not fit comfortably at the GB200 memory profile. GB300 publishes 20 TB of GPU memory and 37 TB of fast memory against 13.4 TB on GB200 NVL72.
When the NVLink domain is what you need
Training and inference that benefit from a 72-GPU scale-up domain without needing the larger memory profile. Both platforms publish the same 130 TB/s of NVLink bandwidth.
When a full rack is more than the workload needs
NVL4-class and other OEM Grace Blackwell configurations bring the architecture into a conventional server footprint, which is often the practical option for sites without rack-scale liquid cooling.
When the CPU coupling is not the point
If the design does not depend on the integrated Grace CPU or the rack-scale NVLink domain, an HGX B200 or B300 server is usually the simpler deployment.
Who builds Grace Blackwell systems
The examples below are systems the manufacturers publish in their own current documentation, reviewed 18 August 2026. They are named to show where the architecture appears, not to indicate that any particular system is available.
| Manufacturer | Published system | As described by the manufacturer |
|---|---|---|
| Dell | PowerEdge XE9712 | GB300 NVL72 system, 48U, 36 Arm-based NVIDIA Grace processors and 72 NVIDIA B300 GPUs |
| Dell | PowerEdge XE8712 | GB200 NVL4 system, 1OU, 2 Arm-based NVIDIA Grace processors and 4 NVIDIA B200 GPUs |
| Lenovo | Lenovo NVIDIA GB300 NVL72 | Rack-scale AI system published in Lenovo's AI server documentation |
| GIGABYTE | NVIDIA GB300 NVL72 GIGAPOD | Rack-scale solution published with direct liquid cooling |
| Supermicro | GB200 NVL72 and GB300 NVL72 solutions | Published within Supermicro's NVIDIA Blackwell portfolio |
What the rack asks of the building
Rack-scale systems arrive as one dense, heavy, liquid-cooled unit. The requirements below are set by the exact configuration purchased, so they are confirmed against that configuration rather than estimated from the platform name.
Rack power and distribution
Firm capacity at the rack, distribution design, protection, metering, and the redundancy target the deployment needs.
CoolingFacility water and heat rejection
Supply temperature, flow, water quality, CDU placement, redundancy, and serviceability for a liquid-cooled rack.
NetworkScale-out fabric
NVLink handles the rack. Connecting racks to each other and to storage is a separate fabric design with its own optics and cabling.
FacilityStructure and access
Floor loading, delivery route, door and lift clearance, and rigging access for a preassembled rack.
Confirm before configuring
- Whether the quote describes a superchip, a node, or a full rack
- Exact platform generation and GPU variant
- Published memory profile for that exact configuration
- Cooling method and facility water requirements
- Rack power requirement and connector design
- Included networking, optics, and cabling
- Software stack, licensing, and support scope
- Installation, commissioning, and acceptance responsibilities
- Seller authority and governing transaction documents
- Export, end-use, and geographic restrictions
Grace Blackwell questions
What is NVIDIA Grace Blackwell?
Grace Blackwell is NVIDIA's architecture pairing Arm-based NVIDIA Grace CPUs with Blackwell-generation GPUs over a coherent link, delivered mainly as rack-scale systems rather than as individual cards. The rack, not the accelerator, is what gets specified, powered, cooled, and installed.
What is the difference between GB200 NVL72 and GB300 NVL72?
Both are 72-GPU, 36-CPU rack-scale systems with 130 TB/s of NVLink bandwidth. GB200 NVL72 uses Blackwell GPUs and publishes 13.4 TB of HBM3E GPU memory. GB300 NVL72 uses Blackwell Ultra GPUs and publishes 20 TB of GPU memory and 37 TB of fast memory. The larger memory capacity on GB300 is the difference that most often decides between them.
What is the difference between a GB200 Superchip and a GB200 NVL72 rack?
The GB200 Grace Blackwell Superchip is one Grace CPU with two Blackwell GPUs, publishing 372 GB of HBM3E and 3.6 TB/s of NVLink bandwidth. GB200 NVL72 is the rack-scale system built from those building blocks, publishing 72 Blackwell GPUs, 36 Grace CPUs, and 130 TB/s of NVLink bandwidth. Quotes and specifications must state which one they describe.
Do Grace Blackwell racks require liquid cooling?
NVIDIA describes GB300 NVL72 as a fully liquid-cooled, rack-scale architecture. Facility water, heat rejection, water quality, CDU placement, redundancy, and serviceability therefore have to exist before the rack is delivered, and the specific requirements come from the exact OEM or NVIDIA configuration being purchased.
Can I compare the FP4 numbers for GB200 and GB300 directly?
Only if the sparsity basis is matched first. NVIDIA publishes GB200 NVL72 NVFP4 as 1,440 PFLOPS sparse and 720 PFLOPS dense, and GB300 NVL72 FP4 as 1,440 PFLOPS with sparsity and 1,080 PFLOPS without sparsity. Comparing a sparse figure to a dense figure produces a result that means nothing.
Which manufacturers build Grace Blackwell systems?
Server manufacturers publish their own Grace Blackwell implementations. Dell publishes PowerEdge XE9712 as a GB300 NVL72 system and PowerEdge XE8712 as a GB200 NVL4 system, Lenovo publishes a Lenovo NVIDIA GB300 NVL72 rack-scale system, and GIGABYTE publishes an NVIDIA GB300 NVL72 GIGAPOD direct-liquid-cooling rack. Configuration, service, and commercial terms differ by manufacturer.
Does SLYD have Grace Blackwell systems in inventory?
Product names on this page are descriptive and do not indicate availability. Whether a specific configuration can be obtained, in what quantity, for what geography, and on what terms is confirmed at the transaction level against current records, with the confirmation date and scope stated.
Sources for the specifications on this page
- NVIDIA, GB200 NVL72 product page. Reviewed 18 August 2026. nvidia.com/en-us/data-center/gb200-nvl72
- NVIDIA, GB300 NVL72 product page. Reviewed 18 August 2026. nvidia.com/en-us/data-center/gb300-nvl72
- Dell, PowerEdge AI servers catalog. Reviewed 18 August 2026. dell.com PowerEdge AI servers
- Lenovo Press, AI servers documentation. Reviewed 18 August 2026. lenovopress.lenovo.com/servers/ai-servers
- GIGABYTE, GIGAPOD rack-scale solutions. Reviewed 18 August 2026. gigabyte.com/Solutions/gigapod
Specifications belong to the manufacturers named and are reproduced with their own caveats. They are not SLYD guarantees of performance, configuration, or availability.
Scope a Grace Blackwell deployment
Share the workload, target scale, site, and timeline. Rack-scale platforms are decided by facility capacity as much as by the compute requirement, so both are worked through together.
Page updated: August 18, 2026