NVIDIA Professional Desktop Computing Solutions for AI Development

Desktop AI Compute Demands

The increasing size and complexity of generative AI models is making development efforts on local systems challenging. Prototyping, tuning, and inferencing large models locally requires large amounts of memory and significant compute performance. As enterprises, software providers, government agencies, startups, and researchers staff up AI efforts, the need for AI compute resources continues to grow.

200B Parameter Models on Your Desk

NVIDIA DGX Spark™ is part of a new class of computers designed from the ground up to build and run AI. Powered by the NVIDIA GB10 Grace Blackwell Superchip and based on the NVIDIA Grace Blackwell architecture, NVIDIA DGX Spark™ delivers up to 1000 TOPS of AI performance to power large AI workloads. With 128 GB of unified system memory, developers can experiment, fine-tune, or inference models of up to 200B parameters. Plus, NVIDIA ConnectX™ networking can connect two NVIDIA DGX Spark™ supercomputers to enable inference on models up to 405B parameters.

To give developers a familiar experience, NVIDIA DGX Spark™ mirrors the same software architecture that powers industrial-strength AI factories. Using the NVIDIA DGX OS with Ubuntu Linux and preconfigured with the latest NVIDIA AI software stack, along with developer program access to NVIDIA NIM™ and NVIDIA Blueprints, developers can hit the ground running using common tools such as Pytorch, Jupyter, and Ollama to prototype, fine-tune, and inference on NVIDIA DGX Spark and seamlessly deploy in the data center or cloud.

By delivering massive performance and capabilities in a compact package, NVIDIA DGX Spark™ lets developers, researchers, data scientists, and students continue to push the boundaries of generative AI.

Built on NVIDIA Grace Blackwell

At the heart of NVIDIA DGX Spark™ is the new NVIDIA GB10 Grace Blackwell Superchip based on the NVIDIA Grace Blackwell architecture optimized for a desktop form factor. GB10 features a powerful NVIDIA Blackwell GPU with fifth-generation Tensor Cores and FP4 support, delivering up to 1000 TOPS of AI compute. GB10 includes a high-performance Grace 20-core Arm CPU to supercharge data preprocessing and orchestration, speeding up model tuning and real-time inferencing. The GB10 Superchip uses the NVLink™-C2C to deliver a CPU+GPU coherent memory model with 5X the bandwidth of PCIe Gen 5.


Work With Large-Parameter AI Models

With 128 GB of unified system memory and support for the FP4 data format, NVIDIA DGX Spark™ can support AI models of up to 200B parameters, enabling AI developers to prototype, fine-tune, and inference large models on their desktop. With built-in NVIDIA ConnectX network technology, two NVIDIA DGX Spark™ systems can beconnected to work on even larger models such as Llama 3.1 405B.


Develop Locally, Deploy Anywhere at Scale

NVIDIA AI Software Stack

• NVIDIA CUDA-X™ libraries for accelerated deep learning and machine learning
• NVIDIA AI Enterprise, offering cloud-native tools, frameworks, and microservices (such as NVIDIA NIM™ and NeMo™) for streamlined AI development and deployment
• NVIDIA AI Workbench, providing a unified, user-friendly environment for managing, developing, and scaling AI projects across local and cloud resources
• Support for leading frameworks like TensorFlow, PyTorch, and JAX, all optimized for NVIDIA hardware

NVIDIA DGX Spark™ provides organizations and developers with a powerful, economical experimentation ground for prototype models, freeing up valuable compute resources in their cluster environments better suited for training and deploying production models. Leveraging the NVIDIA AI platform software architecture makes it possible for NVIDIA DGX Spark™ users to seamlessly move their models from their desktop to DGX Cloud or any accelerated cloud or data center infrastructure with virtually no code changes, making it easier than ever to prototype, fine-tune, and iterate.