Qwen Image 2.1: M3 Ultra vs M5 Ultra vs DGX Spark
Turbo took about eight seconds on both the M5 Ultra and Spark. Here’s what we noticed after trying the same image prompts on all three machines.
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I embedded my whole corpus locally. The cost argument is wrong.
Two full imports of 5,817 chunks on a Mac Studio M3 Ultra, with a small and a large embedding model. Six times the speed, a third of the disk, and a cloud bill of under three cents. What actually justifies keeping this work local.
How AI power users turn prompts into controlled workflows
A serious user delegates tasks; a power user designs and delegates workflows. The six-stage loop, the seven-layer tool stack, one complete WordPress launch — and why the routine work belongs on the Mac, not on the meter.
Local LLM vs DeepSeek Cloud in a real Hermes agent job
One read-only WordPress inventory job through the same Hermes agent, run on local Qwen and Muse on a Mac Studio and on DeepSeek Cloud. What each model did, what it got wrong, and what that says about routing.
Five AI Models, One Coding Job: Where the Local Mac Fell Behind
Five models, one tightly bounded agentic coding job. Four cloud models finished in under 40 seconds; the local 27B on a Mac Studio did not finish. The method and every setting are attached.