They do MoE. They benchmarked GLM 5.3-flash (320B / 18B), and Qwen 3.8-flash-next (125B / 6B). The dense Qwen is only focused (I assume) because it's about the only thing that fits on a 5090, that they can compare the two heads on.
Thank you for this. I wish Apple focused their silicon design on improving the TTFT metrics but coming from an M3 Pro, it still looks laggard compared to Nvidia's TensorCores in the 5090.
Maybe Apple is an acquisition away from changing that balance.
The rumor on Apple's processor roadmap is that they're skipping other M6 variations (all previous generations had Pro and Max, a few had Ultra) in order to focus on the M7 generation for AI reasons. What exactly the M7 improvements are who knows.
The selling point of the M5 Ultra Mac Studio is that you can run much larger models that the 5090 can't without swapping. NVidia aggressively segments the market on VRAM for this reason. That's why a 5090 has an MSRP of ~$2k (but good luck getting one for less than $4k) while a 6000 Pro, which is basically a 5090 with 96GB of RAM has now soared beyond $15k where 3-6 months ago it was more like $10-11k. A 6000 Pro has the same memory bandwidth but slightly more CUDA units (IIRC ~24k vs ~21k).
This advantage won't be apparent with a 27B model. The 256GB MS can probably run the newer Flash models locally, something you can't do on a 5090.
I don't think we'll get a successor to the 5090 until late 2028, maybe even 2029. I'm basing this on the launch date of the 5000 series and that we haven't got a midcycle refresh yet. Rumor has it the chips are ready but the 3GB RAM modules are 3-4x the price of the 2GB modules used on the current cards.
Apple should see a Mac Studio major update in 2028. That might even force NVidia's hand. But it's really impossible to say what the state of the market will be 2-3 years from now. It may have completely crashed. I suspect not however.
The interesting thing will be when the bandwidth demands start forcing HBM memory onto these home/enthusiast solutions.
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.
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.
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
Yeah, anyone who thinks local AI is going to save them money is likely to be disappointed, at least if they want to run models that are even remotely capable.
Plenty of other reasons to get excited about it local AI, but I don't think cost is one of them.
Maybe you are using a local model to go after some Millennium Prize problem and you don't want OpenAI to take your work and use it to win the prize for themselves? $15k might be a bargain.
And, yes, I know a current local model wasn't going to solve the Navier-Stokes problem, but I'm just using it as an example where privacy might be valuable.
Hard to guess, it can go either way. If you will need to be in a syndicate to use non-sterilized models, that mac makes sense. But if there is mandatory registration of personal cyberarms, you risk going to mines once they check you purchases. You could try to play normie and pretend you simply wanted to show off, by keeping your actual work on external disk, but that leaves traces on system. Counting on someone in the Gap renting you gray iron works as long as you can swap credits. Still, this gear is tiny. Put it in your e-car, with uplink, and leave it at uncle's farm. Discreet.
I think we all expect the heavy subsidized subscriptions to end or significantly increase in price at some point, but it could be years from now and I'd rather spend a similar figure on an hypotetical Mac Studio M8 Ultra, or whatever more advanced competitor that will have likley appeared by that time.
A more apples-to-apples comparison would be with API cost in OpenRouter at the same tok/s rate for the same models that you can run locally, maybe.
> "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.
Also: ~30 token/s on GLM 5.3-flash, locally.
/meta Here's a CSS filter that stops those nuisance chart animations,
Maybe Apple is an acquisition away from changing that balance.
https://www.macrumors.com/2026/06/25/2027-macs-m7-chips/
This advantage won't be apparent with a 27B model. The 256GB MS can probably run the newer Flash models locally, something you can't do on a 5090.
I don't think we'll get a successor to the 5090 until late 2028, maybe even 2029. I'm basing this on the launch date of the 5000 series and that we haven't got a midcycle refresh yet. Rumor has it the chips are ready but the 3GB RAM modules are 3-4x the price of the 2GB modules used on the current cards.
Apple should see a Mac Studio major update in 2028. That might even force NVidia's hand. But it's really impossible to say what the state of the market will be 2-3 years from now. It may have completely crashed. I suspect not however.
The interesting thing will be when the bandwidth demands start forcing HBM memory onto these home/enthusiast solutions.
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.
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.
That’s like 12 years worth of OpenAI Pro subscriptions
Plenty of other reasons to get excited about it local AI, but I don't think cost is one of them.
And, yes, I know a current local model wasn't going to solve the Navier-Stokes problem, but I'm just using it as an example where privacy might be valuable.
Specially since one can pay half right now to OpenAI and sign a 12 year iron clad contract for uninterrupted service delivery of OpenAI Pro.
A more apples-to-apples comparison would be with API cost in OpenRouter at the same tok/s rate for the same models that you can run locally, maybe.
I didn't expect this to make the 5090 to look like a good deal.
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.
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.