Running a task directly in ChatGPT is dramatically faster (12 seconds) than running the equivalent task through the Open Claw agent framework on either device (~30 seconds), largely because Open Claw's flexible, layered architecture adds overhead that a closed, optimized system like ChatGPT avoids.

5:38for these kinds of workloads. But, if you're like me and you're used to interacting with ChatGPT or Claude or Gemini, then waiting 30 seconds for a simple task can feel pretty slow. So, I ran the same release summary task directly in Chat GPT using a comparable model. The result came back in 12 seconds on both an M4 Max MacBook Pro and an iPhone 16 Pro. That's a pretty significant gap.

6:05Given everything we've talked about, that shouldn't be too surprising. First off, those are substantially more expensive devices. But, hardware is only part of the story. I suspect that Open Claw itself accounts for a significant portion of the difference. Open Claw is a general-purpose agent framework with lots of hooks, abstractions, and layers designed for maximum flexibility and extensibility. While Chat GPT is a closed system that is heavily optimized for performance and

6:34responsiveness. So, while this experiment started as a hardware comparison, it's clear that the software stack plays a huge role in the overall experience. Another thing that this experiment really highlights for me is why people mostly talk about vibes when evaluating agents. Real benchmarking of these systems is hard. In this case, the biggest source of variation wasn't the thing I was trying to investigate, the hardware, but rather it was the agent

7:01itself. Different tool choices, different plans, and different execution paths often had a bigger impact on runtime, a much bigger impact on runtime in fact, than whether the task was running on a VPS or the Rubik's Pi. And beyond the agent, at least for these workloads, the harness matters just as much as the hardware. So, where does this leave me? For me, there are three practical takeaways. First, I'm probably not switching to a

7:26setup like this for my everyday interactive AI usage. For that, running Chat GPT, Claude, or Gemini directly on my laptop or phone is simply faster and more convenient. That said, I do see a lot of value in systems like Open Claw for asynchronous workloads, things that run on schedules, things that run on triggers, things that gather information, summarize content, or perform background automation while I'm doing something else. For those kinds of