The numbers I was most interested in are tucked away in a chart towards the bottom - the speed comparison of the Mac Studios v.s. a RTX 5090:

  Qwen3.8 27B tokens/sec generation speed

  Prompt size    8K    64K   128K   256K
  RTX 5090 PC    59    51    44     n/a
  M5 Ultra       48    39    32     24
  M3 Ultra       31    23.5  20     15

While I know it's not apples to apples, the target comparison right now is 2x DGX Sparks. Similar price, 256gb. The conversation has focused on memory bandwidth vs. compute in agentic loops, so for most people the raw numbers will mean less than the "time per task" in coding benchmarks.

This is a great article and bodes well for the M5, but we should expect more like this comparing to other platforms before we truly understand where it fits.

This is great as a first look, but the author is not a developer, so we don't yet know whether a dev can be as productive with local models on M5 Mac Studio compared to a 20x subscription plan.

I'm also curious about any new low hanging optimization opportunities in the kernels for this new hardware.

It's already clear to me that M5 Mac Studio is more cost-effective than anything you can run on open router, assuming decent utilization.

The M5 Mac Studio will be the most cost effective way to run uncensored cyber capable open agents.

An exciting tipping point will be if programmers can get an Astra-Ultra like experience all week with this hardware. That would be a real sense where this hardware exceeds the value of even 20x cloud subscriptions.

On Apple website it says 512GB memory option is available in October. I guess bumping to that one would cost additional 4-6k US$. So an Ultra with 2TB storage would be north of 15k US$.

That’s like 12 years worth of OpenAI Pro subscriptions

The model being tested is 18k as configured.

I didn't expect this to make the 5090 to look like a good deal.

Imagine spending a trillion dollars on data centers and then reading this article. Nightmare fuel for OpenAI

>Let’s address the elephant in the room first: why bother with local AI at all when cloud frontier models are better and often faster?

Ehh, the actual elephant in the room is:

"why bother with local AI at all when you can lease a GPU for $5/hr?"

To which the answer is you shouldn't bother, unless you have a bunch of money to throw at hobby projects.

$12,299

> "It also happens to be a Mac, with an operating system that looks nice and doesn’t suck"

Yes Apple has some of the best hardware out there, albeit overpriced. But the software is such a hindrance and I can't take anyone that states otherwise seriously. If only it had proper Linux support (and the Asahi people do an amazing job but you can reverse-engineer only so many stuff with limited funding, and then you have to do it again for new models). MacOS is good if you just want to have a standard experience, which to be fair is most people. It's good for just setting up an LLM server I guess since the hardware is a perfect fit. I wouldn't touch it otherwise.