Holy shit… it costs $10K but you can get a Mac Studio (the little computer) with as much as 512GB of unified memory. Thats right, that’s RAM that can be used for vRAM. Meaning you can run natively the largest DeepSeek and Llama models with tons of room to spare on this single device.

The acceleration of hardware toward Ai optimization is going to be crazy. I get the sense we will see double, triple, and quadruple the vRAM equivalent (though it’ll all go unified) in just the next couple of years of product iterations.

Running huge LLMs and video/image models locally will get easier and easier.

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Btw every indication suggest this could run ChatGPT as well. I don’t think we know exactly how much RAM is required, but considering the comparative models, seems like a very safe bet that you could run their best model natively on this machine.

Crazy

Pinging nostr:nprofile1qqsw9n8heusyq0el9f99tveg7r0rhcu9tznatuekxt764m78ymqu36csxjejf , what’s the total vRAM in that monster you built?

72gb but sadly it's not unified, only max 24gb per card, so I can't do big models

The biggest limitation here is the stuff that still has to have CUDA/Nvidia to run. It’s not a huge amount, but enough to create a noticeable friction.

Still really hard not to entertain this TBH 😂😅😬

Maybe next ath 😎

Tbh kinda worth it

Literally almost bought one this week

Worth it?

Deep infra costs cents, why even bother with overpriced apple walled garden?

nostr:nprofile1qyfhwumn8ghj7ctvvahjuat50phjummwv5q32amnwvaz7tm9v3jkutnwdaehgu3wd3skueqqyzu7we2xhgry2mknq8v7227yn7jguu9xhu3g90n6rtnjj3mpyq3ackdvvhl i've seen reports that theoretically you can get up to 20t/s with this setup, practically might be less so there might be better ways to spend 10k to get more juice out of the hw (tho smaller model)

I would probably prioritize the larger models, 20t/sec seems fine, especially for what I’d be more likely to use it for (Whisper, Florence, Hunyuan, Stable Diffusion) where the LLM is mostly a go between and/or “organizer.”

But I’d probably also change how I use most of my Ai tools if I could run the largest models, so it might suddenly become something I would notice because I changed how I was using things.

I'm gonna wait for nvidia digits first, while much smaller vram if the original price point will be roughly on point you could get 128gb vram for around $3k (obviously it will be more) but i'm curious to see how price/performance will compare, specially if you could get multiple Digits for the same amount

Yeah I was thinking hard about that one too. But I’m not sure they were going to offer the 128GB at the $3K price. If they actually are then that’s awesome, I’ll get 3 of the damn things, lol. But the wording made me think “oh it STARTS at $3K”

yeah unlikely. but i also want blackwell for other reasons, gives you full tee in a gpu 🥳

also there's one crucial difference too, i think its gonna be impossible to get your hands on any nvidia hardware when they release it, like try getting jetson anywhere

full screenshot with asus version as well

That’s funny I was just jumping back here directly from reserving a double of them 🤣

I’m not 100% certain I’ll get them, but we will see how well I’ve integrated and can utilize everything when it gets here.

haha I reserved a GX10 tho tbh I didn't even find much info about it besides the storage diff

lets see if i'm on the right continent to get it when they become available

I'm not paying 10k for ram buddy .

The RAM is $4,800, the whole thing costs $10K. And if you were looking for something that can be used as vRAM for Ai, that’s probably the lowest price you can get anywhere

If you’re wanting to run AI models then consider upgrading to something like this:

https://corticallabs.com/cl1.html

🫣

What the hell is that!?

It's taking the "artificial" out of artificial intelligence.

If you think that's wild, check out their paper published in Cell back in December 2022: "In vitro neurons learn and exhibit sentience when embodied in a simulated game-world"

https://www.cell.com/neuron/fulltext/S0896-6273(22)00806-6

DeepSeek R1 is 700GB. If you quantize it, you lose in quality.