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NVIDIA DGX Spark | DGX personal AI computer, designed to build and run AI | 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 1 petaFLOP1 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.2 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 easily move work to the data center or cloud.

By delivering incredible 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.