[smallnamespace]

An 14-inch M4 Max Macbook Pro with 128GB of RAM has a list price of $4700 or so and twice the memory bandwidth.

For inference decode the bandwidth is the main limitation so if running LLMs is your use case you should probably get a Mac instead.

[dialogbox]

Why Macbook Pro? Isn't Mac Studio is a lot cheaper and the right one to compare with DGX Spark?

[AndroTux]

I think the idea is that instead of spending an additional $4000 on external hardware, you can just buy one thing (your main work machine) and call it a day. Also, the Mac Studio isn’t that much cheaper at that price point.

[dialogbox]

> Also, the Mac Studio isn’t that much cheaper at that price point.

In the list price, it's 1000 USD cheaper. 3,699 vs 4,699 I know a lot can be relative but that's a lot for me for sure.

[AndroTux]

Fair. I looked it up just yesterday so I though I knew the prices from memory, but apparently I mixed something up.

[MomsAVoxell]

Being able to leave the thing at home and access it anywhere is a feature, not a bug.

The Mac Studio is a more appropriate comparison. There is not yet a DGX laptop, though.

[AndroTux]

> Being able to leave the thing at home and access it anywhere is a feature, not a bug.

I can do that with a laptop too. And with a dedicated GPU. Or a blade in a data center. I though the feature of the DGX was that you can throw it in a backpack.

[MomsAVoxell]

The DGX is clearly a desktop system. Sure, it's luggable. But the point is, it's not a laptop.

[pantalaimon]

How are you spending $4000 on a screen and a keyboard?

[AndroTux]

You're not going to use the DGX as your main machine, so you'll need another computer. Sure, not a $4000 one, but you'll want at least some performance, so it'll be another $1000-$2000.

[pantalaimon]

> You're not going to use the DGX as your main machine

Why not?

[BoredPositron]

Because Nvidia is incredibly slow with kernel updates and you are lucky if you get them at all after just two years. I am curious if they will update these machines for longer than their older dgx like hardware.

[smallnamespace]

I didn't think of it ;)

Now that you bring it up, the M3 ultra Mac Studio goes up to 512GB for about a $10k config with around 850 GB/s bandwidth, for those who "need" a near frontier large model. I think 4x the RAM is not quite worth more than doubling the price, especially if MoE support gets better, but it's interesting that you can get a Deepseek R1 quant running on prosumer hardware.

[ChocolateGod]

People may prefer running in environments that match their target production environment, so macOS is out of the question.

[bradfa]

The Ubuntu that NVIDIA ship is not stock. They seem to be moving towards using stock Ubuntu but it’s not there yet.

Running some other distro on this device is likely to require quite some effort.

[ZiiS]

I think the 'environment' here is CUDA; the OS running on the small co-processor you use to buffer some IO is irrelevant.

[pjmlp]

It still is more of a Linux distribution than macOS will ever be, UNIX != Linux.

[deviation]

It's a hoop to jump through, but I'd recommend checking out Apple's container/containerization services which help accomplish just that.

https://github.com/apple/containerization/

[ChocolateGod]

You're likely still targeting Nvidia's stack for LLMs and Linux's containers on MacOS won't help you there.