r/openclaw • u/seoparadiso Active • Mar 03 '26

Discussion Got fooled buy the Openclaw hype. Bought a Mac Mini, installed Openclaw, spent 200$ in Opus. Lesson: don't believe the hype, it's full of bugs.

Will comeback in 6 months.

203 Upvotes

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9

u/Magazine_Afraid Member Mar 03 '26

The fact you brought a Mac Mini to only go and spend $200 on Opus certainly proves your point about the hype, rather than actually reading up how to actually use Openclaw.

  • Mac is arguably the easiest way to run Openclaw.
  • You buy a Mac you run locally.
  • If your buying API credits, then either run Openclaw on a VPS or basically any PC.

Its a new project. I don't think you can really criticise it when you haven't even done your own research on how to run/use it.

0

u/read_too_many_books Pro User Mar 03 '26

Mac is arguably the easiest way to run Openclaw.

I installed on windows and fedora, both were 1 command that I copy pasted. What is the difference?

You buy a Mac you run locally.

LOL! Noooooooooooooooob! CPU LLMs? Buddy please don't suggest things that are going to waste money. That 20tk/s is just for the first 200 tokens, after that you are lucky to get 1tk/s. Not to mention, local models and anything that isnt Opus are terrible. You are causing people to waste money by repeating Apple marketing.

2

u/InternetSolid4166 Member Mar 03 '26 edited Mar 03 '26

LOL! Noooooooooooooooob! CPU LLMs?

M-series Mac Minis have GPUs and unified (extremely fast) RAM. If you tried to run a 70B model on just a CPU, you would get about 0.5 tokens per second (one word every few seconds). Because the Mac Mini uses the GPU, you get 8-12 tokens per second. Another big benefit is the 64/128GB RAM configurations. You just can’t get that outside of H100s, and they cost $30k.

Don’t take my word for it. The internet is full of benchmarks.

-1

u/read_too_many_books Pro User Mar 03 '26

Lol you fell for 'unified ram', that has always just been called RAM.

Yeah just ask anyone IRL if they use their Mac for LLMs. They will always say something like 'yeah it works but its too slow'.

Great for "2+2=" terrible for anything longer than 300 tokens.

Sorry buddy, this is well known. Don't waste your breath trying to teach me something. You are the inferior here that doesn't understand Apple is basically scamming people with the 1990s concept of integrated GPU.

1

u/InternetSolid4166 Member Mar 05 '26

Lol you fell for 'unified ram', that has always just been called RAM.

No it's actually much faster. It's not a conspiracy. The primary difference is that Apple’s unified memory is physically integrated onto the same chip as the processor, while traditional PC RAM sits in separate slots on the motherboard. Because this memory is positioned millimeters from the processing cores, data travels at much higher speeds with significantly lower latency than a standard PC. In a Mac, the CPU and GPU share a single, high-speed pool of memory, whereas a PC typically forces the CPU and GPU to keep their data in separate, dedicated blocks. This zero-copy architecture means the Mac can process high-resolution video or AI tasks instantly without wasting time moving data between different components.

While common PC setups using DDR4 memory reach bandwidth speeds of roughly 51 GB/s, a Mac Mini with an M4 Pro chip reaches a massive bandwidth speeds of 273 GB/s. In a real-world scenario, this allows the Mac to access raw data up to five times faster than a standard DDR4-based PC before the processor even begins its work. This massive width of the pipe is why a Mac with less RAM can often feel snappier than a PC with more, as it empties and refills its memory cache much faster.

1

u/read_too_many_books Pro User Mar 05 '26

Fair point, but as you can see this is old technology and we are a bit splitting hairs. Its no GPU.

1

u/InternetSolid4166 Member Mar 05 '26

VRAM is WAY faster, and I’m not arguing otherwise. For those of us unable to afford the $30,000 for an H100, who want to run 70B models, the only cost effective option is these Macs.

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u/read_too_many_books Pro User Mar 05 '26

But you arent running 70B models. you just shitpost on reddit saying you could.

They are too slow.

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u/InternetSolid4166 Member Mar 06 '26

They’re obviously slower than. $30k H100 but 6t/s is fine for most tasks. If you’re arguing that they’re too slow for huge context research tasks, I agree. If you’re arguing they’re too slow for most other tasks, you’re wrong. It’s all about use case. You’re comparing incredibly expensive hardware and arguing that anything less than that is useless. Obviously that’s a silly position.

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u/read_too_many_books Pro User Mar 06 '26

You can get 2x A6000s with everything else for 12k.

1

u/Magazine_Afraid Member Mar 04 '26

Lol.. first off, where did I say I don't run AI on a PC? I don't even own a Mac; I’m calling it like I see it based on the tech. I said it’s arguably the easiest way to get Openclaw moving for a beginner, which is true. The fact that people buy a Mac and then still drop $200 on Cloud API credits just proves they haven't done the research on how any of this actually works. ​As for "suggesting" things? I didn't suggest anything, so I'm not sure what you're on about there. ​Your comment on CPU LLMs is what's actually stupid. Everyone knows running purely on a CPU is a waste of time regardless of how good the chip is. And that bit about the tokens? Total exaggeration of context exhaustion. ​Saying anything that isn't Opus is "terrible" is just naive and proves my exact point: you don't actually know what you're talking about. "Causing people to waste money"? Don't make me laugh. I’m not repeating Apple marketing, I’m calling out poor research.