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GX10 vs MacBook Pro M4 Max: - Price: $3k / $5k - Memory: same (128GB) - Memory bandwidth: ~273GB/s / 546GB/sec - SSD: same (1 TB) - GPU advantage: ~5x-10x depending on memory bottleneck - Network: same 10Gbe (via TB) - Direct cluster: 200Gb / 80Gb - Portable: No / Yes - Free Mac included: No / Yes - Free monitor: No / Yes - Linux out of the box: Yes / No - CUDA Dev environment: Yes : No
How is the monitor "free" if the Mac costs more?
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.
It 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/se…
Earlier quoted context omitted.
It gives you a very good idea of the capability of the models you'll be running on it!
It doesn't give a good idea of anything. We already know it has 128GB unified memory from the first bullet point on the page.
Earlier quoted context omitted.
It gives you a very good idea of the capability of the models you'll be running on it!
It doesn't give a good idea of anything. We already know it has 128GB unified memory from the first bullet point on the page.
This bit of the FAQ was such a non-answer to their own FAQ, you really have to wonder: >> 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.
> This bit of the FAQ was such a non-answer to their own FAQ, you really have to wonder: You don't have to wonder: I bet they're using generative AI to speed up delivery velocity.
Why is every computer listing nowadays look the same with the glowing golden and blue chip images and the dynamic images that appear when you scroll down. Please give me a good old html table with specs will ya?
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All Sparks only have a memory bandwidth of 270 GB/s though (about the same as the Ryzen AI Max+ 395), while the 3090 has 930 GB/s. (Edit: GB of course, not MB, thanks buildbot)
The 3090 also has 24gb of ram vs 128gb for the spark
Seems this is basically DGX Spark with 1TB of disk so about $1000 bucks cheaper. DGX Spark has not been received well (at least online, Carmack saying it runs at half the spec, low memory bandwidth etc.) so perhaps this is way to reduce buyers regret, you are out only $3000 and not $4000 (with DGX Spark).
Some of the stuff in the Carmack thread made it sound like it could be due to thermals, so maybe could reach or come a lot closer to, but not sustain, and if this has better cooling maybe it does better? I might be off on that.
Earlier quoted context omitted.
It doesn't give a good idea of anything. We already know it has 128GB unified memory from the first bullet point on the page.
GP was subtly implying that the text was written by an LLM (running in the very same Ascent GX10).