Elon Musk Gets Just-Launched NVIDIA DGX Spark: Petaflop AI Supercomputer Lands at SpaceX

The future of AI took flight at Starbase, Texas - where NVIDIA CEO Jensen Huang hand-delivered the first DGX Spark to Elon Musk, chief engineer at SpaceX.

Amid towering engines and gleaming steel, Huang walked past rows of engineers who waved and grinned. Moments later, Musk appeared in the cafeteria, greeting staff, opening donuts and chips for kids, and grabbing a slice of pizza. Huang joined him, recounting the story of delivering the first DGX system to OpenAI - and how DGX Spark takes that mission further.

Imagine delivering the smallest supercomputer next to the biggest rocket, Huang said with a laugh.

The handoff came as SpaceX prepared for the 11th test of Starship - the world's most powerful launch vehicle - fusing the spirit of exploration with the power of AI.

Built for developers, researchers and creators, DGX Spark brings supercomputer-class performance beyond the data center - ready to grab and go.

Nine years ago, NVIDIA bet on the future of AI with NVIDIA DGX-1. Today, that bet goes beyond the data center with the handoff to Musk coming amid the 11th test of SpaceX's Starship, the world's most powerful launch vehicle.

From robotics labs to creative studios, DGX Sparks are landing where ideas happen putting petaflop AI within arm's reach of everyone.

This blog will be updated as DGX Spark systems land from Ollama in Palo Alto to Arizona State's robotics lab, from Refik Anadol's studio to the hands of Jo Mardall at Zipline. Each delivery is a new chapter in the story of AI.

What's Inside DGX Spark? A Supercomputer in the Palm of Your Hand

It's the size of a piece of origami paper, and the thickness of a hardcover book. It acts like a rocket engine for AI.

DGX Spark isn't just compact - it's dense with possibility. Inside its 1.2 kg chassis is a full-blown AI supercomputer built to take AI beyond the data center and into the hands of those who create.

At its core:

NVIDIA GB10 Grace Blackwell Superchip - delivering up to 1 petaflop of AI performance at FP4 precision.

128GB of unified CPU-GPU memory - so developers can prototype, fine-tune and run inference locally without bouncing between machines or cloud instances.

NVIDIA ConnectX networking for clustering and NVIDIA NVLink-C2C for 5x PCIe bandwidth.

NVMe storage for speed and HDMI out for visuals.

And it's not just hardware. DGX Spark comes with the full NVIDIA AI software stack - frameworks, libraries, pretrained models and NVIDIA NIM microservices, ready to power workflows like:

Customizing image-generation models such as FLUX.1

Building vision search and summarization agents with NVIDIA Cosmos

Deploying optimized chatbots using Qwen3

This isn't a dev box. It's a launchpad A petaflop of AI performance within arm's reach for developers, researchers and creators everywhere.

Partners Power Up: DGX Spark Lands Beyond the Data Center

From PC giants to AI pioneers, the diminutive DGX Spark is sure to start something big.

DGX Spark is already in the hands of innovators - from ISVs optimizing their tools to researchers pushing the boundaries of robotics, art and edge AI.

DGX Spark isn't just a breakthrough in size and performance it's a platform built on collaboration. Acer, ASUS, Dell Technologies, GIGABYTE, HP, Lenovo and MSI are rolling out systems that put petaflop AI on your desk, transforming the desktop into an AI launchpad.

These partners deliver more than hardware. They deliver possibility - NVIDIA's full AI stack in a compact form factor that accelerates agentic and physical AI development everywhere ideas happen.

And the rollout doesn't stop at OEMs. DGX Sparks are already lighting up the AI ecosystem. Some highlights:

Ollama in Palo Alto, rewriting how developers run large language models locally.

NYU Global Frontier Lab, where researchers prototype algorithms for privacy-sensitive applications.

Zipline, pushing the boundaries of autonomous delivery.

Arizona State University, running robotics simulations and vision models at the edge.

Refik Anadol's studio, blending art and AI with petaflop performance.

From creative studios to robotics labs, DGX Sparks are landing where imagination meets engineering - taking AI beyond the data center and into the hands of those building what's next.

DGX Spark Ignites a New Era of Desktop AI As DGX Spark systems land across the ecosystem, six early partners are already showing what's possible when petaflop-class AI meets the desktop:

Dell Pro Max with GB10 powered by Grace Blackwell and DGX OS brings data-center class AI at your desk, delivering up to 200B parameters- with unified memory, CUDA and instant scalability. For those needing even more power, connecting two Dell Pro Max with GB10 systems turns them into a single node capable of supporting 400 billion-parameter models.

HP's ZGX Nano G1n AI Station brings serious AI horsepower to the desktop - petaflop-class performance, 128GB unified memory, and full access to NVIDIA's AI stack.

Lenovo ThinkStation PGX brings agentic AI to the desktop. Built for researchers and developers, it runs models up to 200B parameters and seamlessly bridges local prototyping with cloud deployment.

LM Studio is now live on DGX Spark, shipping for Linux on ARM. Developers can spin up private LLM servers, run models like Qwen3 Coder locally, and connect across the network-no cloud required.

Python on DGX Spark is already changing the game. Anaconda's Stanley Seibert dives into unified memory, hybrid compute, and what it means for running billion-row dataframes and billion-parameter models - all locally.

Roboflow brings vision AI to the desktop. With DGX Spark, developers can now train and fine-tune highly accurate computer vision models locally, giving their software the sense of sight and powering intelligent, conne

LINK:	https://blogs.nvidia.com/blog/live-dgx-spark-delivery/...
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