NVIDIA RTX Spark Benchmarking Guide: Battery, Thermals, and Sleep Recovery

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NVIDIA announced RTX Spark on June 1, 2026, a platform designed to run personal AI agents locally on Windows PCs with up to 128 GB of unified memory. While the hardware specifications outline raw capability, they do not reflect real-world performance across everyday usage scenarios such as battery drain or behavior after sleep. A structured benchmarking approach is recommended, covering four lifecycle scenarios: cold start, battery loop, lid-close interruption, and thermal steady state. Particular attention is given to correctness after sleep, as a resumed AI agent must verify whether a tool action completed before the interruption to avoid erroneous retries. Testers are advised to publish their full lifecycle test conditions alongside results, so that peak specs are not mistaken for actual user experience.

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