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Artificial Analysis benchmarks NVIDIA RTX Spark laptop on local agent workloads

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Artificial Analysis tested a prototype 15-inch Surface Laptop Ultra with an RTX Spark N1X chip, 128 GB unified memory, and $5,900 price on its AA-AgentPerf-Local workload. The laptop completed Qwen3.8 27B in 18.7 minutes, close to DGX Spark at 17.3 minutes and 2.0x faster than MacBook Pro M5 Pro at 37.6 minutes.

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NVIDIA's RTX Spark N1X puts up to 128 GB of unified memory and a Blackwell GPU in a Windows laptop. In our first AA-AgentPerf-Local results, an RTX Spark laptop completes our local agent workload on Qwen3.8 27B in 18.7 minutes

RTX Spark's N1X chip is essentially the GB10 from DGX Spark (20-core Arm CPU, 6,144-core Blackwell GPU), with up to 128 GB of memory at 300 GB/s. We tested a prototype 15-inch Surface Laptop Ultra (128 GB, $5,900), plugged in with Windows set to high-performance mode, using NVIDIA's published llama.cpp recipes where available

Key results:

➤ On Qwen3.8 27B the RTX Spark laptop finishes our default workload (8 recorded agent tasks, 168 model turns) in 18.7 minutes, close to DGX Spark (17.3), 2.0x faster than the MacBook Pro (M5 Pro, 64 GB, 37.6) and 1.8x faster than the AMD Ryzen AI Halo (34.5). The GeForce RTX 5090 desktop is fastest, at 4.9 minutes

➤ On Qwen3.6 35B A3B it takes 7.6 minutes, close to DGX Spark (7.3), and 1.6x faster than the MacBook Pro (11.9)

➤ On Ling 3.0 Flash, the largest current model we test, it takes 15.3 minutes, close to DGX Spark (14.9) and 1.6x faster than the Ryzen AI Halo (25.1). Its 77 GB of weights do not fit on the MacBook Pro or the RTX 5090

Read the full analysis: https://artificialanalysis.ai/articles/nvidia-rtx-spark-agentperf-local

Source: Artificial Analysis · x.comPublished · added here