When compared head-to-head on identical agent tasks, the Rubik Pi and a cloud VPS perform roughly equivalently, with run-to-run variation in the agent's own behavior mattering more than the hardware itself.
After running short and complex agent tasks multiple times, the narrator concludes the Rubik Pi and the Digital Ocean VPS are roughly equivalent performers — differences between runs came from the agent's own decisions, not the hardware. ✦ AI generated
Narrator · The TWIML AI Podcast · 2026-06-22 · original ↗
starts at this moment · 5:15
A more rigorous approach to benchmarking would require a lot more runs and perhaps rejecting outliers, but it didn't really take that for me to see that the Rubik Pi is competitive to the VPS that I've been running for months. That said, there's one thing I need to be super clear about. If you're comparing the Rubik Pi and the VPS in isolation, they're roughly equivalent for these kinds of workloads.
verbatim transcript · starts at 5:15
5:15sub-agents to write the code. A more rigorous approach to benchmarking would require a lot more runs and perhaps rejecting outliers, but it didn't really take that for me to see that the Rubik Pi is competitive to the VPS that I've been running for months. That said, there's one thing I need to be super clear about. If you're comparing the Rubik Pi and the VPS in isolation, they're roughly equivalent
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
- ·Rubik Pi is competitive to a Digital Ocean VPS
- ·Run-to-run variation comes from agent decisions, not hardware
- ·Conclusion holds for both short and complex agent tasks
- ·Agent behavior varies more between runs than the platform does
- ·Formal benchmarking would need more runs and outlier rejection
- ·But the pattern was clear without rigorous stats