Don't buy a Mac Mini for OpenClaw before seeing these benchmarks
Mike Codeur
On social media, I kept seeing the same advice over and over: if you want to do AI seriously, buy a Mac Mini.
And every time I asked a slightly skeptical question about that advice, I got the same reaction: are you stupid or what? It is made for running local models. Have you never used Ollama?
The problem is that people often mix up two very different things:
- running a local model in a clean demo
- running a real AI assistant with memory, tools, a large context window, and orchestration
What I wanted to test was not a chatbot. I wanted to test OpenClaw in real conditions.
What I benchmarked
| Setup | Machine | Goal |
|---|---|---|
| Local Apple | MacBook Pro M4 Max 64 GB | test Apple unified memory with large context |
| Local Nvidia | RTX 5080 + Ollama | test raw local performance and KV cache impact |
| Cloud | VPS + Claude API | test real agentic usage without heavy compromise |
One important detail: if my MacBook Pro M4 Max 64 GB struggles, the Mac Mini that everyone recommends is not magically going to do better.
The real problem is agentic context
A real agentic setup includes system identity, rules, skills, tools, memory, and sometimes 30,000 to 60,000 tokens of context. That changes the question completely: does the machine still hold up when you load the full system?
What the benchmarks actually show
1. The Mac is impressive... up to a point
Apple's big advantage is unified memory. But as soon as you inject a real agentic context, response times blow up. It is not just about raw speed, it is about context prefill cost.
2. The RTX 5080 is powerful... as long as everything fits in VRAM
Performance is impressive when the model fits cleanly on the card. But once you factor in the KV cache, long context, and RAM offloading, performance can collapse much faster than people expect.
3. Cloud still sets the reference point for a full assistant
More stable latency, better handling of large context, no hardware gymnastics. The real question is not just can I run a model? It is: can I run my full assistant without lobotomizing it?
What this video shows
Benchmarks across several machines, the limits of local models with large context, why context completely changes how results should be interpreted.
-> Don't buy a Mac Mini for OpenClaw
The right question to ask before buying
Do not just ask: can it run Ollama? Ask instead: can it run my real system, with my real context, my real tools, and my real workflows?
Newsletter: I share this kind of insight every week in The Agentic Dev: mkc.sh/the-agentic-dev?utm_source=blog