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System Overview#

Powered by the NVIDIA Grace Blackwell architecture, DGX Spark enables developers, researchers, and data scientists to prototype, deploy, and fine-tune large AI models on their desktop.

Flexible Access and Usage#

The DGX Spark is designed for maximum flexibility in how you access and use it. You can seamlessly switch between different access methods based on your needs:

  • Local Access: Connect a keyboard, mouse, and monitor to work directly on the system

  • Network Access: Access your system from another computer on the same network using SSH, NVIDIA Sync, or remote desktop tools

  • Hybrid Usage: Mix and match access methods - work locally one day and over the network the next, or even simultaneously

All access methods are fully supported and equally capable. Your DGX Spark adapts to your workflow, whether you’re working at your desk with a monitor or accessing it remotely as a network appliance on the same network.

Key Capabilities#

Your DGX Spark enables you to:

  • Run Inference: Deploy models for real-time AI applications

  • Develop AI Models: Train and fine-tune models with up to 200 billion parameters

  • Process Data: Handle large datasets with high-performance computing

  • Experiment Freely: Test new ideas without cloud computing costs

  • Scale Workloads: Connect multiple systems for larger projects

System Architecture#

The DGX Spark is built on NVIDIA’s Grace Blackwell architecture, providing:

  • Unified Memory: 128 GB of high-bandwidth memory for large models

  • High-Performance Computing: 20-core ARM64-based processor with integrated GPU

  • Advanced Connectivity: Wi-Fi 7, 10 GbE, CX7 NIC, and multiple I/O options

  • Compact Form Factor: 150mm x 150mm x 50.5mm desktop design

For detailed hardware specifications, see Hardware Overview.

Software#

Your system comes pre-configured with:

  • NVIDIA DGX OS: Optimized operating system for AI workloads

  • Development Tools: CUDA, cuDNN, and NVIDIA’s development ecosystem

  • Container Support: Docker and NVIDIA Container Runtime for easy deployment

  • NGC Integration: Access to NVIDIA’s container registry

For detailed software information, see Software.

Getting Started#

To begin using your DGX Spark:

  1. Initial Setup: Follow the Initial Setup - First Boot to configure your system

  2. Explore Examples: Try sample workloads to understand capabilities

  3. Configure Development Environment: Set up your preferred tools and frameworks

  4. Start Building: Begin your AI development projects

Note

For the most up-to-date tutorials and examples, visit https://build.nvidia.com/spark. This site is regularly updated with new content and serves as the primary resource for practical guides and use cases.