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From the FAQ… doesn’t seem promising when they ask and then evade a crucial question. > What is the memory bandwidth supported by Ascent GX10? AI applications
by abtinf 11mo ago
From the FAQ… doesn’t seem promising when they ask and then evade a crucial question.
> What is the memory bandwidth supported by Ascent GX10? AI applications often require a bigger memory. With the NVIDIA Blackwell GPU that supports 128GB of unified memory, ASUS Ascent GX10 is an AI supercomputer that enables faster training, better real-time inference, and support larger models like LLMs.
- LeifCarrotson 11mo agoIt sounds good, but it ultimately fails to comprehend the question: ignoring the word "bandwidth" and just spewing pretty nonsense. Which is appropriate, given the applications! I see that they mention it uses LPDDR5x, so bandwidth will not be nearly as fast as something using HBM or GDDR7, even if bus width is large. Edit: I found elsewhere that the GB10 has a 256bit L5X-9400 memory interface, allowing for ~300GB/sec of memory bandwidth.
- guerrilla 11mo agoIt doesn't sound good at all. It sounds like malicious evasion and marketing bullshit.
- exe34 11mo agoIt gives you a very good idea of the capability of the models you'll be running on it!
- guerrilla 11mo agoIt doesn't give a good idea of anything. We already know it has 128GB unified memory from the first bullet point on the page.
- epolanski 11mo agoI think the previous user made a joke about LLMs spewing nonsense on top of AI bs thus this product being quite fitting.
- darkwater 11mo agoGP was subtly implying that the text was written by an LLM (running in the very same Ascent GX10).
- BikiniPrince 11mo agoWith a little tinkering we can just have the AI gaslight us about it’s capabilities.
- guerrilla 11mo agoAh! Thanks for explaining. haha
- tuhgdetzhh 11mo agoFor comparison, the RTX 5090 has a memory bandwidth of 1,792 GB/s. The GX10 will likely be quite disappointing in terms of tokens per second and therefore not well suited for real-time interaction with a state-of-the-art large language model or as a coding assistant.
- curvaturearth 11mo agoWritten by a LLM?
- Youden 11mo agoThey seem to have another FAQ here that gives a real answer (273GB/s): https://www.asus.com/us/support/faq/1056142/ https://www.asus.com/us/support/faq/1056142/
- suprjami 11mo agoNow we can see why they avoided giving a straight answer. File this one in the blue folder like the DGX
- stogot 11mo agoNoob here. Why is that number bad?
- kennethallen 11mo agoRunning LLMs will be slow and training them is basically out of the question. You can get a Framework Desktop with similar bandwidth for less than a third of the price of this thing (though that isn't NVIDIA).
- embedding-shape 11mo ago> Running LLMs will be slow and training them is basically out of the question I think it's the reverse, the use case for these boxes are basically training and fine-tuning, not inference.
- kennethallen 11mo agoThe use case for these boxes is a local NVIDIA development platform before you do your actual training run on your A100 cluster.
- abtinf 11mo agoMy mac laptop has 400gb/s bandwidth. LLMs are bandwidth bound.
- fancyfredbot 11mo agoThey have failed to provide answers to other FAQ as well. The answers are really awkward and don't read like LLM output which I'd expect to be much more fluent. Perhaps a model which was lobotomized through FP4 quantisation and "fine tuning" on one of these.