4 ms·
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 doe
by threeducks 1y ago
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 does not look like a good choice, as there are cheaper alternatives with better performance.
- CamperBob2 1y agoMy 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_cant_we_just_use_nvidia_jetson_agx_thor/nawxbk2/ https://old.reddit.com/r/LocalLLaMA/comments/1n0xoji/why_can...
- altspace 1y agoI’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.
- KeplerBoy 1y agoThe 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.