NVIDIA RTX Spark
NVIDIA RTX Spark is a compact AI “superchip” designed to run AI agents and models locally on Windows PCs — in laptops and compact desktops. It combines an NVIDIA Blackwell RTX GPU (up to 6,144 CUDA cores) with an NVIDIA Grace CPU (up to 20 Arm cores), connected at 600 GB/s.
The platform delivers up to 1 PFLOP of FP4 AI performance and up to 128 GB of unified memory, enabling local execution of models that do not fit on a typical machine. RTX Spark runs the full NVIDIA CUDA software stack.
RTX Spark is a product DISTINCT from NVIDIA DGX Spark: RTX Spark targets consumers and personal agents on Windows, whereas DGX Spark is a developer machine running Linux. Preorders opened on October 7, 2026, laptops became available on October 16, 2026, and compact desktops from November 2026. Systems are offered by Acer, ASUS, Dell, HP, Lenovo, Microsoft, MSI and Gigabyte.
Classification
AI Accelerator · serves as: High-level compute, AI Inference.
Which group NVIDIA RTX Spark belongs to and how it is built
Compute Modules is a subcategory of hardware components that provide processing power for robotic systems. It encompasses onboard computers, single-board computers (SBCs), AI accelerators, embedded processors, GPU/NPU compute modules, and other units responsible for processing sensor data and executing control logic. These modules form the foundation of modern autonomous, humanoid, and perception-capable robots.
An AI Accelerator is a specialized hardware component designed for efficient execution of artificial intelligence computations, particularly neural network inference, computer vision processing, and sensor data analysis. In robotics, AI accelerators are used to run perception models, object recognition, image segmentation, planning, and other tasks that require high computational throughput under constrained power budgets. They may take the form of dedicated NPU, TPU, VPU, or GPU chips, or specialized embedded modules.
Technical specification
full stack
full stack
Relations
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