NVIDIA GB10 Grace Blackwell Superchip (DGX Spark Module)
Brand: NVIDIA | Category: Accessories & Components
SKU: GB10-SUPERCHIP | Part #: GB10-SUPERCHIP | MPN: GB10-SUPERCHIP
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About the NVIDIA GB10 Grace Blackwell Superchip (DGX Spark Module)
The NVIDIA GB10 Grace Blackwell Superchip (part number GB10-SUPERCHIP) delivers unified CPU-GPU compute architecture with up to 1 PFLOPS of AI performance in FP4 precision, enabling transformative throughput for enterprise AI workloads within the integrated DGX Spark desktop chassis. The superchip combines 72 Arm Neoverse V2 CPU cores with NVIDIA Blackwell GPU architecture, connected via fifth-generation NVLink-C2C interconnect delivering 900 GB/s bidirectional bandwidth for seamless CPU-GPU coherent memory access. This unified memory architecture eliminates data bottlenecks critical to large-scale model training and inference deployment.
Enterprise AI infrastructure teams leveraging NVIDIA's software ecosystem—including CUDA, TensorRT, NVIDIA NIM, cuDNN, PyTorch, JAX, DeepSpeed, and NCCL—will benefit from broad precision support (FP4, FP8, FP16, BF16, TF32, FP32, INT8) and specialized accelerator engines including the Transformer Engine and second-generation NVDLA. The system runs NVIDIA DGX OS, an Ubuntu-based Linux operating system optimized for AI workloads, and supports multi-DGX Spark clustering via NVLink Switch for scaled multi-node configurations. The LPDDR5X unified memory pool eliminates traditional CPU-GPU memory separation, streamlining development cycles for enterprise AI applications. Contact Omnixon Global to request detailed specifications and availability for the GB10-SUPERCHIP.
Enterprise Deployment Scenarios
- Enterprise AI development environments requiring integrated CPU-GPU coherence with 900 GB/s unified memory bandwidth
- Edge inference clusters leveraging multi-node NVLink Switch interconnect for distributed model serving
- Research computing initiatives in large language models, transformer architectures, and custom AI frameworks
- Production AI pipelines utilizing NVIDIA TensorRT and NVIDIA NIM for optimized inference deployment
- Data science teams standardizing on CUDA and PyTorch within a single unified memory compute platform
Technical Specifications
| Brand | NVIDIA |
| Category | Accessories & Components |
| SKU | GB10-SUPERCHIP |
| Part Number | GB10-SUPERCHIP |
| Condition | New |
| Manufacturer Part Number | GB10-SUPERCHIP |
| Module Name | NVIDIA GB10 Grace Blackwell Superchip |
| Platform | NVIDIA DGX Spark |
| GPU Architecture | NVIDIA Blackwell |
| CPU Architecture | NVIDIA Grace (72-core Arm Neoverse V2) |
| AI Performance (FP4) | Up to 1 PFLOPS |
| Chip-to-Chip Interconnect | NVLink-C2C (fifth-generation), 900 GB/s bidirectional bandwidth |
| CPU Cores | 72 Arm Neoverse V2 cores |
| System Memory Type | LPDDR5X unified memory (CPU + GPU coherent) |
| Unified Memory Bandwidth | 900 GB/s (NVLink-C2C coherent) |
| GPU Memory | Shared unified memory pool with Grace CPU via NVLink-C2C |
| Accelerator Engines | NVIDIA Transformer Engine, second-generation NVDLA |
| Supported Precisions | FP4, FP8, FP16, BF16, TF32, FP32, INT8 |
| Software Ecosystem | CUDA, cuDNN, TensorRT, NVIDIA NIM, NCCL, DeepSpeed, PyTorch, JAX |
| Multi-Node Interconnect | NVLink Switch support for multi-DGX Spark clustering |
| Operating System Support | NVIDIA DGX OS (Ubuntu-based Linux) |
| Form Factor | Integrated system-on-module (SoM) within DGX Spark desktop chassis |
| Target Segment | Enterprise AI development, edge inference, research computing |
Frequently Asked Questions about NVIDIA GB10 Grace Blackwell Superchip (DGX Spark Module)
What does the NVIDIA GB10 Grace Blackwell Superchip (DGX Spark Module) do?
The NVIDIA GB10 Grace Blackwell Superchip (DGX Spark Module) is enterprise IT hardware deployed in production data centers, server rooms, and edge sites across the GCC and EMEA region.