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Posted by acossta 9 hours ago

A Dynamic and Distributed Virtual GPU Cloud Built on Idle Apple Silicon Devices(machinelearning.apple.com)
205 points | 90 commentspage 2
nsagent 5 hours ago|

  Future work will extend Minions to support distributed model training in addition to inference
That could allow enthusiasts to pool compute resources on devices like Mac Studios, Mac Minis, etc to perform large scale federated training. While it'll be massively inefficient compared to running in a data center, it could democratize open weights models even more.

It would be especially useful for RL post training of existing models, which is where much of the agentic abilities arise from.

curt15 5 hours ago|
Something like the old folding@home distributed molecular dynamics calculations?
ElijahLynn 3 hours ago||
Millions of Mac users could make passive income renting out their plugged in GPU and compute...
bigyabai 3 hours ago||
No, they really can't. There is no market for Apple Silicon GPU compute, largely because the fastest Mac GPUs you can buy are arguably a waste of TSMC's silicon.

Look at it like this: a maxed-out M5 Ultra Mac Studio starts at $6,799, and the iGPU benchmarks similar to an $800 RTX 4070 Ti SUPER. That's a 3nm SOC getting outperformed by a 5nm dGPU; Apple Silicon is years behind Nvidia's consumer offerings, and that's before we even compare with datacenter-grade DGX/Instinct GPUs.

badc0ffee 2 hours ago|||
The combination of "maxed-out" and "starts" is kind of confusing, but I found the machine you're talking about - M5 Ultra with the 36-core CPU and 80-core GPU, 96 GB RAM, 1 TB SSD.

It has 6x the RAM, 2x the memory bandwidth and looks like it totally outclasses the RTX 4070 Ti SUPER. I did some searching and it looks like a close comparison would be the older M3 Ultra Mac Studio, although again, with a lot less RAM.

sleepybrett 2 hours ago|||
sorry $1300 for that 4070 now
1-6 3 hours ago||
Sounds like Elon Musk's plan of Tesla owners selling idle compute on their cars.
jacquesm 7 hours ago||
There are a lot of parallels between the DGX (and clones) series devices and these Apple devices, maybe it would be possible to rope in the DGX boxes as well. There's lots of them out there and I'm pretty sure not all of them have high utilization.
MomsAVoxell 5 hours ago|
The DGX are certainly making a case for a new workstation platform to compete with Apple. The user experience is on par, and the local model capabilities are very appealing in many use cases. I've been happy to have had a pair to play with anyway .. I sure hope the price comes down and Nvidia expand the concept ..
jacquesm 4 hours ago||
For now the prices seem to be only going up. It is complete madness. At the same time: I'm kind of happy about that. It means that lots of people and small to mid sized organization have a very nice incentive to make low end hardware perform better. If you look at how much effort is being poured into model compression and clever VRAM management schemes on the low end it is quite impressive. And plenty of those are compounding.

I wished they had a bit more memory bandwidth though, this is quite annoying.

simbas 9 hours ago||
That's why the button is on the underside.
djoldman 8 hours ago||
Paper:

https://arxiv.org/pdf/2610.12970

Shortest promoted paper I've seen from a FAANG.

nico 7 hours ago||
Would love to build something like this but for classification models that run on CPU. Like a “Classify @ Home” p2p compute network, to which people could contribute their machines and see what work is being done

Building the classification part now :) https://jeffyclassify.com/

gempir 8 hours ago||
Interesting, so this is basically Apple's version of exo ? https://github.com/exo-explore/exo
skhameneh 8 hours ago||
Reading the “paper”, this is just a job runner built on Ollama. Exo, and the teams at Apple that built the foundations Exo uses, actually use modern distributed compute.
jacquesm 7 hours ago||
I don't get why they didn't use llama.cpp instead.
cmdrk 7 hours ago||
Apple has reinvented cycle scavenging about 40 years later.
janandonly 6 hours ago||
I remember seeing this at a presentation two or three years ago. I’m surprised it wasn’t rolled out right after?
skhameneh 8 hours ago|
I’m a bit disappointed in the lack of depth (and use of Ollama): https://arxiv.org/html/2610.12970v1

Apple has released some small models previously that seemed genuinely great, along with some quality research/efforts. I’m just not seeing the same level of depth here, am I missing something?

neuronexmachina 7 hours ago||
I think it's basically just a write-up of something they're already using internally.
serhack_ 8 hours ago||
true, shame on apple for the paper quality
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