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A comment on NVIDIA DGX Spark In-Depth Review: A New Standard for Local AI Inference. Parent comment

Re:NVIDIA DGX Spark In-Depth Review: A New Standard for Loca... by threeducks on Tuesday October 14, 2025 @04:10AM (#45577454)
More precisely, the RTX 5090 has a memory bandwidth of 1792 GB/s, while the DGX Spark only has 273 GB/s, which is about 1/6.5.

For inference, the DGX Spark is trash and there are cheaper alternatives with better performance.

[ Parent | on HN ]
Re:NVIDIA DGX Spark In-Depth Review: A New Standard for Loca... by CamperBob2 on Tuesday October 14, 2025 @01:13PM (#45582481)
My understanding is that the Jetson Thor is just as good a platform, and likely more readily available.

Then there's the Mac Studio, which outdoes them in all respects except FP8 and FP4 support. As someone on Reddit put it: https://old.reddit.com/r/LocalLLaMA/comments/1n0xoji/why_can...

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Re:NVIDIA DGX Spark In-Depth Review: A New Standard for Loca... by altspace on Tuesday October 14, 2025 @04:49PM (#45584658)
I’ve been thinking the same… I have jetson Thor and only difference I can imagine is the capability to connect two DGX sparks together… but then I’d rather go for RTX pro 6000 instead of buying two DGX spark units, because I prefer the higher memory bandwidth, more Cuda cores, tensor cores and RT cores over 256 GB memory for my use case.
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Re:NVIDIA DGX Spark In-Depth Review: A New Standard for Loca... by KeplerBoy on Wednesday October 15, 2025 @03:34AM (#45589196)
The jetson thor seems to be quite different. The Thor whitepaper lists 8 TFlop/s of FP32 compute where the DGX sparks seems to be closer to 30 TFlop/s. Also 48 SMs on the Spark vs 20 on the Jetson.

The DGX seems vastly more capable.

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