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MacBook Pro with M5 Pro and M5 Max

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Re: MacBook Pro with M5 Pro and M5 Max

#91
post #12

I typed “RAM” to search for it and boy they hammer home how lucky I am to be getting 1TB SSD standard, but no mention of RAM anywhere on this page. Anyway, the MacBook Pro starts with 16GB of RAM. It’s $400 to go from 16GB to 32GB. Interestingly, 36-128GB models are showing as “currently unavailable” on the store page, and you can’t even place an order for them right now? But for anyone curious, it’s quoting $5099 fo…

>Anyway, it starts with 16GB of RAM. $400 to go from 16GB to 32GB Interesting that this hasn't budged since the memory shortages appeared.

Fair chance that Apple has price/purchase agreements already in place. Consumers are left to fight over the excess capacity after megabuyers get their orders filled.

Re: MacBook Pro with M5 Pro and M5 Max

#92
post #67

Earlier quoted context omitted.

I think its just marketing, and the marketing is working. Look how many people bought Minis and ended up just paying for API calls anyway. (Saw it IRL 2x, see it on reddit openclaw daily) I don't mind it, I open Apple stock. But I'm def not buying into their rebranding of integrated GPU under the guise of Unified Memory.

I've tried to use a local LLM on an M4 Pro machine and it's quite painful. Not surprised that people into LLMs would pay for tokens instead of trying to force their poor MacBooks to do it.

What are the other specs and how's your setup look? You need a minimum of 24GB of RAM for it to run 16GB or less models.

Re: MacBook Pro with M5 Pro and M5 Max

#93
post #6

128gb of memory, it's a nice change for Apple not to lag in that department for once, wonder what such a machine will cost though.

128gb was there for a while. I am kind of disappointed they do not have 256gb option.

Same here. If the had 256GB option I'd pull a trigger. Now I might be looking for alternatives.

Re: MacBook Pro with M5 Pro and M5 Max

#94
post #7

The hardware looks amazing! Too bad they will ship with Tahoe installed. I’m not upgrading until I see in which direction the next Mac OS release goes

Just yesterday, my colleague's mac Time Machine couldn't recover backup and they had to reinstall everything.

But I think this predates Tahoe.

Re: MacBook Pro with M5 Pro and M5 Max

#95

Earlier quoted context omitted.

Closing Tabs in Safari till takes more than a second though. And if you hold Cmd-W to close all of them it just completely locks up and crashes. Still not fixed since the release of Safari 26. Literally unusable

I’ve been running the macOS 26.4 beta and have none of these issues.

I will say that 26.4 beta 2 was the first time I've regretting using betas since Sonoma beta 2. The Sonoma beta ruined the firmware on my machine and Apple had to replace the logic board; the latest Tahoe beta broke all networking on my machine and I had to erase the installation to fix everything. I've since dropped off the beta train for the time being.

I already left the beta train on my iPhone because I had too many issues getting my grocery apps to allow me to place orders without going to my laptop and doing it in a web browser.

Re: MacBook Pro with M5 Pro and M5 Max

#96
post #7

The hardware looks amazing! Too bad they will ship with Tahoe installed. I’m not upgrading until I see in which direction the next Mac OS release goes

This. I have been a big (and loud) fan of M-series hardware from the beginning, but if Apple is going to keep making their software worse, I will find myself lingering on older generations that run Asahi Linux or going back to a traditional x86_64 laptop instead of buying into new generations.

Re: MacBook Pro with M5 Pro and M5 Max

#97

On M4 Max 128GB we're seeing ~100 tok/s generation on a 30B parameter model in our from scratch inference engine. Very curious what the "4x faster LLM prompt processing" translates to in practice. Smallish, local 30B-70B inference is genuinely usable territory for real dev workflows, not just demos. Will require staying plugged in though.

4x faster is about token prefill, i.e. the time to first token. It should be on par with DGX Spark there while being slightly faster than M4 for token generation. I.e. when you have long context, you don't need to wait 15 minutes, only 4 minutes.

Re: MacBook Pro with M5 Pro and M5 Max

#98
post #5

"Scaling up performance from M5 and offering the same breakthrough GPU architecture with a Neural Accelerator in each core, M5 Pro and M5 Max deliver up to 4x faster LLM prompt processing than M4 Pro and M4 Max, and up to 8x AI image generation than M1 Pro and M1 Max." Are they doubling down on local LLMs then? I still think Apple has a huge opportunity in privacy first LLMs but so far I'm not seeing much execution.…

There already are a bunch of task-specific models running on their devices, it makes sense to maintain and build capacity in that area.

I assume they have a moderate bet on on-device SLMs in addition to other ML models, but not much planned for LLMs, which at that scale, might be good as generalists but very poor at guaranteeing success for each specific minute tasks you want done.

In short: 8gb to store tens of very small and fast purpose-specific models is much better than a single 8gb LLM trying to do everything.

Re: MacBook Pro with M5 Pro and M5 Max

#100
post #5

"Scaling up performance from M5 and offering the same breakthrough GPU architecture with a Neural Accelerator in each core, M5 Pro and M5 Max deliver up to 4x faster LLM prompt processing than M4 Pro and M4 Max, and up to 8x AI image generation than M1 Pro and M1 Max." Are they doubling down on local LLMs then? I still think Apple has a huge opportunity in privacy first LLMs but so far I'm not seeing much execution.…

Apple's AI strategy really kind of threads the needle cleverly.

"AI" (LLMs) may or may not have a bubble-pop moment, but until it does Apple get to ride it on these press releases and claims. But if the big-pop occurs, then Apple winds up with really fantastic hardware that just happens to be good at AI workloads (as well as general computing).

For example, image classification (e.g. face recognition/photo tagging), ASR+vocoders, image enhancement, OCR, et al, were popular before the current boom, and will likely remain popular after. Even if LLM usage dries up/falls out of vogue, this hardware still offers a significant user benefit.

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