The DGX Spark is considered the smallest AI supercomputer NVIDIA has built due to its compact design and powerful capabilities. Here are the key factors that contribute to its status:
1. Compact Form Factor: The DGX Spark is designed to fit into a small enclosure, measuring approximately 150 x 150 x 50.5 mm, making it comparable in size to a Mac Mini[6]. This compact size allows it to be easily placed on a desktop, providing powerful AI capabilities in a space-efficient manner.
2. GB10 Grace Blackwell Superchip: At the heart of the DGX Spark is the GB10 Grace Blackwell Superchip, which includes an NVIDIA Blackwell GPU with fifth-generation Tensor Cores and FP4 support. This chip is specifically optimized for a desktop form factor, ensuring that it delivers high performance while maintaining a small size[1][2].
3. High Performance: Despite its small size, the DGX Spark can deliver up to 1,000 trillion operations per second (TOPS) of AI compute, making it suitable for fine-tuning and running advanced AI models such as the NVIDIA Cosmos Reason and GR00T N1 robot foundational models[2][5].
4. Unified Memory and Storage: The DGX Spark comes with 128GB of unified system memory, allowing it to handle AI models with up to 200 billion parameters for inference and fine-tune models up to 70 billion parameters. It also offers up to 4TB of NVMe M.2 storage, providing ample space for data-intensive AI applications[5][6].
5. Energy Efficiency: The system operates at a power consumption of just 170W, making it an energy-efficient solution for AI development compared to larger data center systems[5].
6. Advanced Interconnect Technology: The GB10 Superchip uses NVIDIA NVLink-C2C interconnect technology, which provides a CPU+GPU-coherent memory model with significantly enhanced bandwidth compared to traditional PCIe connections. This technology optimizes performance for memory-intensive AI workloads[2][7].
Overall, the DGX Spark's combination of compact design, high performance, and advanced technology makes it the smallest yet powerful AI supercomputer NVIDIA has developed, catering to the needs of researchers, developers, and data scientists who require robust AI capabilities on their desktops.
Citations:
[1] https://www.theverge.com/news/631957/nvidia-dgx-spark-station-grace-blackwell-ai-supercomputers-gtc
[2] https://nvidianews.nvidia.com/news/nvidia-announces-dgx-spark-and-dgx-station-personal-ai-computers
[3] https://arstechnica.com/ai/2025/03/nvidia-announces-dgx-desktop-personal-ai-supercomputers/
[4] https://www.engadget.com/ai/nvidias-spark-desktop-ai-supercomputer-arrives-this-summer-200351998.html
[5] https://www.maginative.com/article/nvidia-unveils-dgx-spark-and-dgx-station-desktop-ai-supercomputers-for-the-developer-masses/
[6] https://www.youtube.com/watch?v=_14Mvy0KOL0
[7] https://www.investing.com/news/company-news/nvidia-launches-personal-ai-supercomputers-for-desktops-93CH-3934971
[8] https://www.digitimes.com/news/a20250319PD227/nvidia-gtc-ai-supercomputing-2025.html
[9] https://redmondmag.com/Articles/2025/03/18/NVIDIA-Expands-AI-for-Enterprises.aspx
[10] https://techcrunch.com/2025/03/18/nvidia-announces-two-personal-ai-supercomputers/
[11] https://www.reddit.com/r/LocalLLaMA/comments/1jedy17/nvidia_digits_specs_released_and_renamed_to_dgx/
[12] https://www.nvidia.com/en-us/products/workstations/dgx-spark/