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Nvidia DGX Spark

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Re: Nvidia DGX Spark

#111

Post by lhl »

timc3 wrote: post #102
KingOfCoders wrote: post #88

I think it depends on your model size Fits into 32gb: 5090 Fits into 64gb - 96gb: Mac Studio Fits into 128gb: for now 395+ $/token/s, Mac Studio if you don't care about $ but don't have unlimited money for Hxxx This could be great for models that fit 128gb and you want best $/token/s (if it is faster than a 395+).

The 395 although it can be supplied with 128GB can’t use all that for VRAM (unless something has changed in the last couple of weeks).

In Linux, you can set it as high as you want, although you should probably have a swap drive and still be prepared for you system to die if you set it to 128GiB. Here's how you'd set it to 120GiB:

    # This is deprecated, but can still be referenced
    options amdgpu gttsize=122800

    # This specifies GTT by # of 4KB pages:
    #   31457280 * 4KB / 1024 / 1024 = 120 GiB
    options ttm pages_limit=31457280

Re: Nvidia DGX Spark

#112

Post by _zoltan_ »

MBCook wrote: post #67
coder543 wrote: post #18

Earlier quoted context omitted.

This thing has a ConnectX-7, which gives it 2 x 200 Gbps networking. The 10 gig port is far from the fastest network interface on the Spark.

But can you hook that up to a normal PC?

why criticize something in the first place when you clearly have not even looked at the product?

Re: Nvidia DGX Spark

#113

Post by _zoltan_ »

x2tyfi wrote: post #29
MBCook wrote: post #12

I’m not in this space, so I don’t know what’s normal, but I guess I’m a little surprised to see only 10 gig Ethernet for high speed connectivity. Yeah, it’s miles better than WiFi. But if there was something I’d think maybe benefit from Thunderbolt this would’ve been it. The ability to transfer large models or datasets that way just seems like it would be much faster and a real win for some customers.

You’re almost always going to bottleneck on your home internet or upstream ISP, rather than this local interface. That being said, you aren’t going to be waiting too long either way, depending on download speed. Deepseek R1 is 671GB. Multiply by 8 to get into bits: 5368Gb At full 10gbps (which, again, you probably won’t get): 5368Gb / 10gbps = 537 seconds to download 537s / 60 = 8.95 minutes. Call it 10m with overhea…

I have 25 Gbps symmetric ethernet from my ISP (not XGPON). they are talking about rolling out 100 Gbps.

Re: Nvidia DGX Spark

#116

Post by saagarjha »

FirmwareBurner wrote: post #103
nodesocket wrote: post #68

Earlier quoted context omitted.

Once the updated Mac Studio with M4/M5 Ultra comes out, pretty much going to make the DGX irrelevant right?

If that would be true why aren't Mac sales banned in China instead of Nvidia GPUs?

Those are high end GPUs that aren’t comparable

Re: Nvidia DGX Spark

#117

Post by globular-toast »

querez wrote: post #110

"developers can prototype, fine-tune, and inference [AI models]"... shouldn't it be infer ?

Perhaps "infer from"? I was also taken aback by how they just decided to make "inference" a verb, though. A decent writer would have rewritten the sentence to make it work, similar to how a software implementation sometimes just doesn't work out. But apparently that's too much to ask from Nvidia marketing.

Funnily enough things like this show that a human probably was involved in the writing. I doubt an LLM would have produce that. I've often thought about how future generations are going to signal that they are human and maybe the way will be human language changing much more rapidly than it has done, maybe even mid sentence.

Re: Nvidia DGX Spark

#118

Post by pixelpoet »

UncleOxidant wrote: post #90
cherioo wrote: post #24

The mainstream options seem to be Ryzen AI Max 395+, ~120 tops (fp8?), 128GB RAM, $1999 Nvidia DGX Spark, ~1000 tops fp4, 128GB RAM, $3999 Mac Studio max spec, ~120 tflops (fp16?), 512GB RAM, 3x bandwidth, $9499 DGX Spark appears to potentially offer the most token per second, but less useful/value as everyday pc.

> Ryzen AI Max 395+, ~120 tops (fp8?), 128GB RAM, $1999 Just got my Framework PC last week. It's easy to setup to run LLMs locally - you have to use Fedora 42, though, because it has the latest drivers. It was super easy to get qwen3-coder-30b (8 bit quant) running in LMStudio at 36 tok/sec.

Very encouraging result, I'm waiting super anxiously for mine! How much memory did you allocate for the iGPU?

Re: Nvidia DGX Spark

#119

Post by bjackman »

hereme888 wrote: post #49

FP4-sparse (TFLOPS) | Price | $/TF4s 5090: 3352 | 1999 | 0.60 Thor: 2070 | 3499 | 1.69 Spark: 1000 | 3999 | 4.00 ____________ FP8-dense (TFLOPS) | Price | $/TF8d (4090s have no FP4) 4090 : 661 | 1599 | 2.42 4090 Laptop: 343 | vary | - ____________ Geekbench 6 (compute score) | Price | $/100k 4090: 317800 | 1599 | 503 5090: 387800 | 1999 | 516 M4 Max: 180700 | 1999 | 1106 M3 Ultra: 259700 | 3999 | 1540 ____________ Ap…

Note you cannot actually get a 5090 for $1999 that's just the RRP. I believe they actually cost $4k
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