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NVIDIA

NVIDIA DGX Spark™ - Personal AI Desktop Supercomputer – Desktop GB10 Grace Blackwell Chip

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Availability: Only 2 left in stock, order soon!
Fulfilled by Amazon
Arrives Friday, May 1
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Features

  • Supercomputer performance directly to your desk in a compact, energy-efficient design, enabling enterprise-scale AI and high-performance computing right where you need it.
  • The power of Grace Blackwell architecture, delivering up to 1 petaFLOP of AI performance for local model fine-tuning, inference, and analytics, accelerating your time-to-solution.
  • Designed from the ground up to build and run AI, delivering seamless integration of the full NVIDIA AI software stack so you can develop locally and deploy anywhere.
  • NVIDIA DGX Spark gives you the freedom to experiment, prototype, and innovate faster by augmenting laptop, desktop, cloud, or data center resources. With more power to learn, prototype, test, and innovate, NVIDIA DGX Spark delivers exceptional ROI for increased productivity.
  • Use NVIDIA DGX Spark to unlock new ideas and experiment with large models (up to 200 billion parameters at FP4) directly on your desktop with 128GB of unified memory. Empower rapid testing, validation, and iterationdriving innovation in a secure, high-performance setting.

Description

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 petaFLOP 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.

Brand: NVIDIA


Operating System: NVIDIA DGX OS


CPU Model: Cortex


CPU Speed: 3.8 GHz


Cache Size: 24


Graphics Card Description: Dedicated


Graphics Coprocessor: Integrated Graphics


Memory Storage Capacity: 4 TB


Specific Uses For Product: Business, Education


Personal computer design type: Mini PC


Operating System: NVIDIA DGX OS


Specific Uses For Product: Business, Education


Personal Computer Design Type: Mini PC


Color: Gold


Additional Features: 128GB of coherent, unified system memory, 4TB NVME.M2 with self-encryption, ConnectX-7 Smart NIC, NVIDIA GB10 Grace Blackwell Superchip, Up to 1 PFLOPS of FP4 AI performance


Hard Disk Description: SSD


Hardware Interface: Bluetooth, Ethernet, HDMI, USB


Item Dimensions: 9.5 x 9.5 x 6 inches


Video Output Interface: HDMI


Hard Disk Interface: Solid State


Style Name: Minimalist


Video Output: HDMI


Cache Memory Installed Size: 24


Memory Storage Capacity: 4 TB


RAM Memory Installed: 128 GB


RAM Memory Technology: DDR5


Ram Memory Maximum Size: 128 GB


RAM Type: DDR5 RAM


Processor Series: Cortex


Processor Speed: 3.8 GHz


Processor Socket: SoC


Processor Count: 20


Total Usb Ports: 4


Total Number of HDMI Ports: 1


Number of Component Outputs: 1


Human-Interface Input: Keyboard


Keyboard Description: Standard, Wired Keyboard


Keyboard Layout: QWERTY


Brand: NVIDIA


Model Number: DGX Spark


Model Name: NVIDIA DGX Spark


Built-In Media: Power Adapter


Processor Brand: ARM


Model Year: 2025


CPU Model Number: ARM Cortex-X925 + ARM Cortex-A725 Processor


Warranty Description: 1 Year Limited Warranty


UPC: 810152850299


Manufacturer: NVIDIA


Graphics Description: Dedicated


Graphics Coprocessor: Integrated Graphics


Graphics Card Ram: 128 GB


Graphics Ram Type: DDR5 SDRAM


Graphics Card Interface: Integrated


Display Resolution Maximum: 3840x2160


Aspect Ratio: 169


Resolution: 3840 x 2160


Native Resolution: 3840 x 2160


Connectivity Technology: Bluetooth, Ethernet, USB, Wi-Fi


Wireless Network Technology: Wi-Fi


Frequently asked questions

If you place your order now, the estimated arrival date for this product is: Friday, May 1

Yes, absolutely! You may return this product for a full refund within 30 days of receiving it.

To initiate a return, please visit our Returns Center.

View our full returns policy here.

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Top Amazon Reviews

    • Excellent for local LLM research
Excellent for local LLM research. It gave me a shock when it appeared not to boot up after first setting it up. It turned out it just needed some time and started up after a while. That was not at all obvious though. It’s basically silent and it doesn’t have any lights to show that it’s even on. I feel like nvidia could at least have forked out for an off/on light on the case. ... show more
Reviewed in the United States on March 1, 2026 by P. Martin
    • Works well
Depending on the purpose for which you buy the device. But it works well.
Reviewed in the United States on March 27, 2026 by Kirill Keker
    • It broke my heart
Actually, I’m very impressed with this item. It works as deign and I plan to re-buy this in the future when they fix the thermal issue soon as I got everything set up and it loaded and working just the way I wanted it. I ran into this thermal problem where it kept cutting off without notice Crashing without notice that I was running it broke my heart to send it back because I really wanted it. I will buy this again in the future when they fix the thermal issue. I have an issue with the seller. The item kept overheating and I was forced to return it, but the seller charged me $1000 restocking fee so that tells me that they’re gonna put a broken item back on the shelf to resell it to somebody else and charge them a restocking fee if you really want the item buy it if Amazon is selling it or buy it from Nvidia do not under no circumstances buy from Micro Center because they won’t treat you right ... show more
Reviewed in the United States on November 23, 2025 by Victor Williams
    • Powerhouse
Review Image by ooTo
I am pretty knowledgeable with Linux terminal/command prompts which makes it very user friendly for my skill set. I usually SSH in from any of my other computers. For what I don't know, I use different LLM for helping solve the task that I work on. I am currently using at as a hobby dev project on my home lab. Its definitely been a great asset with helping make other agents for other task. I have very large LLM running locally. One of them is helping with discover more about my business and better ways I can run it. Its very quiet very fast. If you are considering ordering one, if you don't have another computer you can login via phone to setup your connection to wifi. It doesn't come with usb-c keyboard or mouse. If you have old USB keyboard and mouse, you will need USB to usb-c converter, if you don't know how to ssh from another computer to the DGX Spark ... show more
Reviewed in the United States on February 21, 2026 by ooTo
    • Great reliable system for AI local models, Highly recommended
Fantastic device, reliable and fast highly recommended
Reviewed in the United States on April 22, 2026 by David A. Nauta
    • SPARK
It is speedy, convenient and easy to install
Reviewed in the United States on April 9, 2026 by D
    • Wifi issues
To the embarrassment of NVIDIA engineers, the WiFi drivers weren't working, and the system wouldn't even finish the initial boot process. I had to boot from a USB stick, set a root password, and fix everything myself. It's a total disgrace.
Reviewed in the United States on April 5, 2026 by Ahiro
    • Great little product, very powerful for it's form factor and size.
This uses the Blackwell GB10 (SM 121) architecture. Currently, mainstream PyTorch stable binaries lack native support for this specific instruction set, so you may need to use NVIDIA’s NGC Docker containers or manually compile from source to enable GPU acceleration. Keep this in mind if your workflow requires a bare-metal installation. ... show more
Reviewed in the United States on February 25, 2026 by Scott M Lawrence

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