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<\/p>\nNews Summary:<\/p>\n
\n\tNVIDIA founder and CEO Jensen Huang delivers DGX Spark to Elon Musk at SpaceX.
\n\tThis week, NVIDIA and its partners are shipping DGX Spark, the world\u2019s smallest AI supercomputer, delivering NVIDIA\u2019s AI stack in a compact desktop form factor.
\n\tAcer, ASUS, Dell Technologies, GIGABYTE, HPI, Lenovo and MSI debut DGX Spark systems, expanding access to powerful AI computing.
\n\tBuilt on the NVIDIA Grace Blackwell architecture, DGX Spark integrates NVIDIA GPUs, CPUs, networking, CUDA libraries and NVIDIA AI software, accelerating agentic and physical AI development.
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NVIDIA today announced it will start shipping NVIDIA DGX Spark\u2122, the world\u2019s smallest AI supercomputer.<\/p>\n
AI workloads are quickly outgrowing the memory and software capabilities of the PCs, workstations and laptops millions of developers rely on today \u2014 forcing teams to shift work to the cloud or local data centers.<\/p>\n
As a new class of computer, DGX Spark delivers a petaflop of AI performance and 128GB of unified memory in a compact desktop form factor, giving developers the power to run inference on AI models with up to 200 billion parameters and fine-tune models of up to 70 billion parameters locally. In addition, DGX Spark lets developers create AI agents and run advanced software stacks locally.<\/p>\n
\u201cIn 2016, we built DGX-1 to give AI researchers their own supercomputer. I hand-delivered the first system to Elon at a small startup called OpenAI \u2014 and from it came ChatGPT, kickstarting the AI revolution,\u201d said Jensen Huang, founder and CEO of NVIDIA. \u201cDGX-1 launched the era of AI supercomputers and unlocked the scaling laws that drive modern AI. With DGX Spark, we return to that mission \u2014 placing an AI computer in the hands of every developer to ignite the next wave of breakthroughs.\u201d<\/p>\n
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DGX Spark brings together the full NVIDIA AI platform \u2014 including GPUs, CPUs, networking, CUDA\u00ae libraries and the NVIDIA AI software stack \u2014 into a system small enough for a lab or an office, yet powerful enough to accelerate agentic and physical AI development. By combining breakthrough performance with the reach of the NVIDIA ecosystem, DGX Spark transforms the desktop into an AI development platform.<\/p>\n
DGX Spark systems deliver up to 1 petaflop of AI performance, accelerated by a NVIDIA GB10 Grace Blackwell Superchip, NVIDIA ConnectX\u00ae-7 200 Gb\/s networking and NVIDIA NVLink\u2122-C2C technology, providing 5x the bandwidth of fifth-generation PCIe with 128GB of CPU-GPU coherent memory.<\/p>\n
The NVIDIA AI software stack is preinstalled to enable developers to start working on AI projects out of the box. With DGX Spark, developers can access NVIDIA AI ecosystem tools including models, libraries, and NVIDIA NIM\u2122 microservices, enabling local workflows such as customizing Black Forest Labs\u2019 FLUX.1 models to refine image generation, creating a vision search and summarization agent using the NVIDIA Cosmos\u2122 Reason vision language model, or building an AI chatbot using Qwen3 that is optimized for DGX Spark.<\/p>\n
To celebrate DGX Spark shipping worldwide, Huang hand-delivered one of the first units of DGX Spark to Elon Musk, chief engineer at SpaceX, today in Starbase, Texas. The exchange was a connection to the supercomputer\u2019s origins, as Musk was among the team that received the first NVIDIA DGX\u2122-1 supercomputer from Huang in 2016.<\/p>\n
Other early recipients of DGX Spark, including Anaconda, Cadence, ComfyUI<\/a>, Docker<\/a>, Google, Hugging Face, JetBrains, LM Studio, Meta, Microsoft, Ollama and Roboflow<\/a>, are testing, validating and optimizing their tools, software and models for DGX Spark.<\/p>\n Research organizations around the world, including the NYU Global Frontier Lab, previewed DGX Spark to boost their AI development.<\/p>\n \u201cDGX Spark allows us to access peta-scale computing on our desktop,\u201d said Kyunghyun Cho, professor of computer and data science at the NYU Global Frontier Lab. \u201cThis new way to conduct AI research and development enables us to rapidly prototype and experiment with advanced AI algorithms and models \u2014 even for privacy- and security-sensitive applications, such as healthcare.\u201d<\/p>\n