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Going deep on local AI performance benchmarking with Apple’s Mac Studio with M5 Ultra taking on Nvidia DGX Spark

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Going deep on local AI performance benchmarking with Apple’s Mac Studio with M5 Ultra taking on Nvidia DGX Spark

Apple’s updated Mac Studio with the M5 Ultra SoC has already proven itself as one of the most powerful systems around, thanks to its 36-core CPU and 80-core GPU with Neural Accelerators for the matrix math operations that drive AI compute. Beyond that raw power, options for up to 512GB of unified memory have many local AI enthusiasts lining up for the 13 to 15 weeks it’ll take for Apple to ship one right now.

But is our tested Mac Studio config worth a whopping $12,300 or more for those folks? We already tested the maxed-out M5 Ultra chip with the popular Qwen 3.8 27B in our initial review, but that compact dense model doesn’t come anywhere close to exercising 256GB of memory. We wanted to fill that pool to the brim with cutting-edge large models like DeepSeek V4.1 Flash 1017 and GLM 5.3 Flash.

We also have some new benchmarks at our disposal to see how the Mac Studio stacks up in agentic tasks on the GPU side in the wake of our review of the Microsoft Surface Laptop Ultra with Nvidia’s RTX Spark chip. So there's much to dig into.

We started our more detailed local AI testing with Artificial Analysis' AgentPerf-Local benchmark. This test plays back recorded inference traces with certain models across a range of agentic AI workloads to gauge performance. Artificial Analysis provides a full breakdown of this workload, but the bulk of its work takes place in prompt processing rather than token generation. As a result, it should favor systems with lots of raw compute, which both GB10 and the M5 Ultra have at their disposal.


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