Benchmark a Personal AI PC Across Battery, Thermals, and Sleep Recovery

Short summary

The article proposes a structured benchmarking framework for personal AI PCs like NVIDIA's RTX Spark, arguing that peak specs don't reveal real-world usability. It defines a test envelope covering device, OS, power mode, model, and runtime, then prescribes four lifecycle scenarios: cold start, battery loop, sleep recovery, and thermal steady state. Correctness after sleep is prioritized, requiring agents to detect whether tool effects completed before sleep or use idempotency keys.

• •Benchmark AI PCs across four lifecycle scenarios: cold start, battery loop, sleep recovery, and thermal steady state
• •Correctness after sleep recovery matters more than peak specs—agents must detect pre-sleep tool completion
• •Publish the full test envelope with results so peak specifications aren't mistaken for user experience

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