NVIDIA RTX Spark N1X 笔记本首份 AA-AgentPerf-Local 测试结果

AA-AgentPerf-Local replays recorded agent sessions on local hardware

RTX Spark puts DGX Spark's chip in a Windows laptop

RTX Spark is NVIDIA’s platform for Windows on Arm PCs, which NVIDIA pitches as built to run AI agents locally. Its N1X chip is essentially the GB10 from DGX Spark (NVIDIA’s own recipe catalogue lists RTX Spark as GB10), with a 20-core Arm CPU, a 6,144-core Blackwell GPU and up to 128 GB of LPDDR5X memory shared between them. In the laptop the memory runs faster, giving 10% more bandwidth than DGX Spark (300 GB/s against 273 GB/s). However, the chip runs at 45 to 80 W (NVIDIA’s stated range for N1X laptops), where GB10 is rated at 140 W.

We tested a prototype 15-inch Surface Laptop Ultra with 128 GB of memory, priced at $5,899.99. It runs Windows 11 on Arm and serves every model with a native Windows build of llama.cpp on the GPU. We ran it plugged in with Windows set to its high performance power mode.

Specifications from NVIDIA’s RTX Spark page and porting guide, NVIDIA’s DGX Spark documentation and Apple as of October 2026, with memory speeds as reported by the systems we tested

Each system runs its own recipe

We run each model with a recipe chosen for each system, using the vendor’s published recipe where one exists, so the runtime, speculative decoding and 4-bit weight format differ between systems. The RTX Spark laptop runs NVIDIA’s llama.cpp recipes for RTX Spark, ported into AA-AgentPerf-Local with NVIDIA’s settings.

The recipe behind each system’s fastest Qwen3.8 27B result

We are also testing more weight formats and runtimes, including smaller 4-bit formats such as IQ4_XS and Inco AI’s Splash, a Metal engine for Apple Silicon that uses DFlash speculative decoding. We will add their results once they pass our accuracy checks, which we will publish soon. Early tests show faster completion times on some systems.

The RTX Spark laptop finishes the workload in 8-19 minutes, depending on the model

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