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by gerdesj
6 days ago
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Actually, its ~119GB usable (I have one). You can shutdown a lot of unneeded services if you only use it remote which will trim a lot more fat. You can enable the RDP service if you don't want to sit in front of it but get a desktop interface. The "shitty" network is 10Gb/s and wifi7! You get a twin QSFP28DDlol+++ (I jest) that each run at 200Gb/s - not for the casual home user but handy at work, although I "only" have 40Gb/s on my switches sigh. With and no switch two you can do a three node cluster with some careful networking. If you want to do more then a switch is needed and it will need to be pretty funky! That said you could wire them up in a circle and use VLANs and MSTP and accept less than 200Gb/s per link. You'll probably need Openvswitch and a lie down afterwards. I'm not a fan of the Gnome desktop but it works well enough and I think the Nvidia customised Ubuntu is well thought out. You get all the complicated NVidia extras pre-installed, along with docker (full fat, not the Ubuntu one) for a fairly quick start. It includes Ubuntu Pro which is free for five systems anyway but its nice to see it pre-installed. You can run quite decent models on this thing see: https://spark-arena.com/ Also see "DS4". We blew abut £4000 on one and it will pay for itself in a few months. I tried pricing up an Apple thingie and the Store wouldn't offer me more than 96Gb of RAM and a delivery date in Q3 at the earliest. Our Spark rocked up next day. They seem to come in 1TB or 4TB SSD variants. 1TB is enough for me and saves a lot of cash - keep an eye on your model downloads and ruthlessly delete old experiments. docker system prune. We went for the Asus variant that has active cooling and I stuck it in the ceiling cable tray over our computer room racks. It sits on 1½" stainless steel mesh with lots of clearance in an actively cooled environment. |
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I should have prefaced my post - I almost bought four Sparks a couple months ago, but ultimately opted to buy two more RTX 6000 Pro Max-Q's.
It was a painful choice because the two 6000's were more expensive than four Sparks, and ultimately gave me only 384 GB VRAM.
It was even more painful when GLM 5.2 was released, and a 4x Spark setup could run it at a decent quant, but 4x 6000's cannot with any headroom.
But the 6k's absolutely destroy the Sparks on prefill and inference speed. Model intelligence is compressing. The smaller VRAM pool will matter less over time than slower prefill/inference speed.
That is to say, I'm sure we'll end up with <500B parameter models that are Fable-level in the next 8 months or so. Performant quants of those will fit comfortably in 384 GB.