6 ms·
Asus Ascent GX10
- RachelF 1y agoThese very narrow speed measurements are getting out of hand: 1 petaFLOP using FP4, that's 4 petaFLOPS using FP1 and infinite petaFLOPS using FP0.
- simlevesque 1y agoI really wish I had the kind of money to try my hands at it.
- hamdingers 1y agoYou can rent GPUs from many providers for a few bucks an hour.
- uyzstvqs 1y agoEven cheaper, unless you want the really high-end enterprise stuff. You can run ComfyUI pretty comfy for $0.30 to $0.40 per hour, if AI art is your goal.
- maxbaines 1y agoLooks like a pretty useful offering, 128Gb Memory Unified, with the ability to be chained. IN the Uk release price looks to be £2999.99 Nice to see AI Inference becoming available to us all, rather than using a GPU ..3090etc. https://www.scan.co.uk/products/asus-ascent-gx10-desktop-ai-supercomputer-gb10-blackwell-superchip-1tb-ssd-128g-lpddr5x-200gb-connec https://www.scan.co.uk/products/asus-ascent-gx10-desktop-ai-...
- BoredPositron 1y agoI would hold my horses and see if the specs are actually true and not overblown like for the spark otherwise there are better options.
- exasperaited 1y agoAnd if waiting six months is possible, do that. Asus make some really useful things, but the v1 Tinker Board was really a bit problem-ridden, for example. This is similarly way out on the edge of their expertise; I'm not sure I'd buy an out-there Asus v1 product this expensive.
- eightysixfour 1y agoThis is a Spark, so it is not going to be any different.
- atwrk 1y agoAll 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)
- buildbot 1y agoI believe you mean GB/s?
- postalrat 1y agoThe 3090 also has 24gb of ram vs 128gb for the spark
- Gracana 1y agoYou'd have to be doing something where the unified memory is specifically necessary, and it's okay that it's slow. If all you want is to run large LLMs slowly, you can do that with split CPU/GPU inference using a normal desktop and a 3090, with the added benefit that a smaller model that fits in the 3090 is going to be blazing fast compared to the same model on the spark.
- Jackson__ 1y agoEh, this is way overblown IMO. The product page claims this is for training, and as long as you crank your batch size high enough you will not run into memory bandwidth constraints. I've finetuned diffusion models streaming from an SSD without noticeable speed penalty at high enough batchsize.
- cmxch 1y agoAt that price (roughly 4000 USD), one could build a full HBM powered Xeon system from the Sapphire Rapids generation. Either build a single socket system and give it some DDR5 to work alongside, or go dual socket and a bit less DDR5 memory.
- deleted 1y ago[deleted]
- npalli 1y agoSeems 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).
- cma 1y agoSome 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.
- nxobject 1y agoI'd love to see how far shucking it and using aftermarket cooling will go. Or perhaps it's hard-throttled for market segmentation purposes?
- simlevesque 1y agoSimon Willison seems to like his:https://til.simonwillison.net/llms/codex-spark-gpt-oss https://til.simonwillison.net/llms/codex-spark-gpt-oss
- colordrops 1y ago"I don't think I'll use this heavily"
- jandrese 1y agoPerformance wise it was able to spit out about half of a buggy version of Space Invaders as a single HTML file in roughly a minute.
- badgersnake 1y agoI’m pretty sure I could spit out something that doesn’t work in half a minute.
- buildbot 1y agoFunny to wakeup and see this on the front page - I literally just bought a pair last night for work (and play) somewhat on a whim, after comparing the available models. This one was available the soonest & cheapest, CDW is giving 100 off even, so 2900 pre tax.
- nik736 1y agoWhich models will this be able to run at an acceptable token/s rate?
- simlevesque 1y agogpt-oss:120b https://til.simonwillison.net/llms/codex-spark-gpt-oss https://til.simonwillison.net/llms/codex-spark-gpt-oss
- hamdingers 1y agoAm I missing it or is there no information about performance? Looking for a tokens/sec
- simlevesque 1y agoHe didn't give that info but the transcript linked at the end shows how much time was spent for each query.
- aseipp 1y agoRight now I get 59 tok/sec on GPT-OSS 120B using Unsloth's dynamic 4-bit quants, via llama.cpp https://news.ycombinator.com/item?id=45881049 https://news.ycombinator.com/item?id=45881049
- brian_herman 1y agoCouldn't you buy a Mac Ultra with more memory for the same price?
- simlevesque 1y agoCuda is king
- MangoToupe 1y agoStill? Really? Why?
- baby_souffle 1y agoInertia. Almost everybody else was asleep at the wheel for the last decade and you do not catch up to that kind of sustained investment overnight.
- embedding-shape 1y agoFor how shit it all is, it's still the easiest to use, with most available resources when you inevitable need to dig through stuff. Just things like nsight GUI and available debugging options ends up bringing together a better developer experience compared to other ecosystems. I do hope the competitors get better though because the current de facto monopoly helps no-one.
- whywhywhywhy 1y agoBetter support than MPS and nothing Apple is shipping today can compete with even the high end consumer CUDA devices in actual speed.
- MangoToupe 1y agoPresumably the second point is irrelevant if you're choosing among devices with unified memory.
- 1y ago
- 7734128 1y agoIf you touch the image when scrolling on mobile then it opens when you lift your finger. Then when you press the cross in the corner to close the image, the search button behind it is activated. How can a serious company not notice these glaring issues in their websites?
- tomalaci 1y agoAI powered business value provider frontend developers.
- the_real_cher 1y agoEnshittification. Its not that they dont notice. They dont care.
- janlukacs 1y agobut it has AI in it.
- speedgoose 1y agoOn desktop, clicking on an image opens it but then you can't close it, and the zoom seems to be glitchy. But I'm not surprised, this is ASUS. As a company, they don't really seem to care about software quality.
- schainks 1y agoTaiwanese companies still don't value good software engineering, so talented developers who know how to make money leave. This leaves enterprise darlings like Asus stuck with hiring lower tier talent for numbers that look good to accounting.
- fodkodrasz 11mo agoWait until you start using an ASUS computer, and hit the BIOS/UEFI issues... I learned the hard way that ASUS translates do "don't buy ever again".
- cbsmith 1y agoThis 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.
- palmotea 1y ago> 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.
- cbsmith 1y agoI guess that's the kindest possible interpretation. The other interpretation is that the answer is not a good one.
- palmotea 11mo ago> I guess that's the kindest possible interpretation. The other interpretation is that the answer is not a good one. If they wanted to do that, they should have just omitted the question from their FAQ. An evasive answer in a FAQ is a giant footgun, because it just calls attention to the evasion.
- cbsmith 11mo agoIt's possible the FAQs were generated by one process and the answers were generated by another.
- abtinf 1y agoFrom 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 1y 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.
- embedding-shape 1y agoI wonder why they even added this to the FAQ if they're gonna weasel their way around it and not answer properly? > 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. Never seen anything like that before. I wonder if this product page is actually done and was ready to be public?
- skrebbel 1y agoMaybe they had a local llm write it but the memory bandwidth was too low for a decent answer.
- porphyra 1y agoProbably LLM slop, but also it's the same GB10 chip as the DGX Spark so why would the memory bandwidth be significantly different?
- baby_souffle 1y agoAs far as I can tell these are all the same hardware just different enclosures. I'm not sure why Nvidia went this route given that they have a first party device. Usually you only see this when the original manufacturer doesn't want to be in the distribution or support game.
- joelthelion 1y ago"Nvidia dgx os", ugh. It would be a lot more enticing if that thing could run stock Linux.
- porphyra 1y agoit's basically just linux with a custom kernel and cuda preinstalled
- simlevesque 1y agoYeah that's a bummer. They do the same for all their boards like the Jetson Nano.
- colechristensen 1y agoI assume the driver code just isn't in mainline linux and installing the correct toolchain isn't always easy. Having it turnkey available is nice and fundamentally new hardware just isn't going to have day 1 linux support. You're free to lift the kernel and any drivers/libraries and run them on your distribution of choice, it'll just be hacky.
- CamperBob2 1y agoWhat would be the advantages, exactly?
- CamperBob2 1y agoGuess I have my answer.
- aseipp 1y agoIt's just Ubuntu with precanned Nvidia software, otherwise it's a "normal" UEFI + ACPI booting machine, just like any x86 desktop. People have already installed NixOS and Fedora 43, and you can even go ahead and then install CUDA and it will work, too. (You might be able to forgo the nvidia modules and run upstream Mesa+NVK, even.) It's very different from Jetson and much more like a normal x86 desktop. The kernel is patched (and maintained by Canonical, not Nvidia) but the patches hanging off their 6.17-next branch didn't look outrageous to me. The main hitch right now is that upstream doesn't have a Realtek r8127 driver for the ethernet controller. There were also some mediatek-related patches that were probably relevant as they designed the CPU die. Overall it feels close to full upstream support (to be clear: you CAN boot this system with a fully upstream kernel, today). And booting with UEFI means you can just use the nvidia patches on $YOUR_FAVORITE_DISTRO and reboot, no need to fiddle with or inject the proper device trees or whatever.
- Stevvo 1y agoThese AI boxes resemble gaming consoles in both form factor and architecture, makes me curious if they could make good gaming machines.
- Havoc 1y agoLikely not. Bit like the AI focused cards get their ass kicked by much cheaper gaming cards. The focus has diverged Plus ofc software stack for gaming on this isn’t available
- bigyabai 1y agoEh, I wouldn't be so hasty: 1) This still has raster hardware, even ray tracing cores. It's not technically an "AI focused card" like the AMD Instinct hardware or Nvidia's P40-style cards. 2) It kinda does have a stack. ARM is the hardest part to work around, but Box86 will get the older DirectX titles working. The GPU is Vulkan compliant too, so it should be able to leverage Proton/DXVK to accommodate the modern titles that don't break on ARM. The tough part is the price. I don't think ARM gaming boxes will draw many people in with worse performance at a higher price.
- vinkelhake 1y agoThat would depend on your idea of "good". It would be an upstream swim in most regards, but you could certainly make it work. The Asahi team has shown that you can get steam working pretty well on ARM based machines. But if gaming is what you're actually interested in, then it's a pretty terrible buy. You can get a much cheaper x86-based system with a discrete GPU that runs circles around this.
- whatever1 1y agoAny good ideas for what these can be used for? I am still trying to think a use case that a Ryzen AI Max/MacBook or a plain gaming gpu cannot cover.
- MurkyLabs 1y agoA GPU cluster would work better but if you're only testing things out using CUDA and want 200GB networking and somewhat low power all in one this would be the device for you
- cmrdporcupine 1y agoAI stuff aside I'm frankly happy to see workstation-class AArch64 hardware available to regular consumers. Last few jobs I've had were for binaries compiled to target ARM AArch64 SBC devices, and cross compiling was sometimes annoying, and you couldn't truly eat your own dogfood on workstations as there's subtle things around atomics and memory consistency guarantees that differ between ISAs. Mac M series machines are an option except that then you're not running Linux, except in VM, and then that's awkward too. Or Asahi which comes with its own constraints. Having a beefy ARM machine at my desk natively running Linux would have pleased me greatly. Especially if my employer was paying for it.
- addaon 1y agoLaptop-class bandwidth without that annoying portability.
- aseipp 1y agoIt's very, very good as an ARM Linux development machine; the Cortex-X925s are Zen5 class (with per-core L2 caches twice as big, even!) and it has a lot of them; the small cores aren't slouches either (around Apple M1 levels of perf IIRC?) GB10 might legitimately be the best high-performance Linux-compatible ARM workstation you can buy right now, and as a bonus it comes with a decent GPU.
- sneilan1 1y agoDoes anyone have any information on how much this will cost? Or is it one of those products where if you have to ask you can't afford it.
- sbarre 1y agoLots of existing posts in this discussion talking about prices in various regions and configurations.
- DiabloD3 1y agoWhat a shame. This would have been a much more powerful machine if it was wrapped around AMD products. At least with this, you get to pay both the Nvidia and the Asus tax!
- wmf 1y agoIn this case the Asus "tax" is negative $1,000.
- jauntywundrkind 1y agoReally interested to see if anyone starts using the fancy high end Connect-X 7 NIC in these DGX Spark / GB10 derived systems. 200Gbit RDMA is available & would be incredible to see in use here.
- WhitneyLand 1y agoGX10 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
- tassadarforaiur 1y agoOn the networking side. M4 max does have thunderbolt 5, 80gbps advertised. Would ip over TB not allow for significantly faster interconnects when clustering Macs?
- WhitneyLand 1y agoMade the correction to 80Gb/sec thank you. W.r.t ip, the fastest I’m aware of is 25Gb/s via TB5 adapters like from Sonnet.
- tgma 1y agoYou should not be using an adapter to get IP over Thunderbolt. Just connect a Thunderbolt5 cable to both machines.
- WhitneyLand 1y agoFor point to point sure, but if you want to connect multiple machines in an actual fabric you’ll need some kind of network interop. The Asus clustering speed is not limited to p2p.
- tgma 1y agoFair enough. On the other hand you have more thunderbolts to make up a clique mesh of seven point to point Macs.
- 1y ago
- Aurornis 1y agoThese are primarily useful for developing CUDA targeted code on something that sits on your desk and has a lot of RAM. They're not the best choice for anyone who wants to run LLMs as fast and cheap as possible at home. Think of it like a developer tool. These boxes are confusing the internet because they've let the marketing teams run wild (or at least the marketing LLMs run wild) trying to make them out to be something everyone should want.
- mahirsaid 1y agois this another product they're pushing out for publicity. I mean how much testing has been done for this product. Need more specs and testing results to illuminate capabilities, practicality.
- dinkleberg 1y agoThis is a tangent, but the little pop up example for their ai chat bot to try and entice me to use it was something along the lines of “what are the specs?” How great would it be if instead of shoving these bots to help decipher the marketing speak they just had the specs right up front?
- arcanemachiner 1y agoBut how would that boost their KPIs for user engagement and AI usage?
- mey 1y agoWhy not burn down some tree's and show the wrong information instead of putting a simple table?
- yndoendo 1y agoI find all these Popup Assistant Bots as bad User Experience. No, I don't want to use your assistant and your are forcing me to pointlessly click on the close button. Some times they event hide viable information during their popup. They seem to be the reincarnation of 2000s popups; there to satisfy a business manager versus actually being a useful tool.
- varispeed 1y agoI was really hyped about this, but then I watched videos and it's just meh. What is the purpose of this thing?
- oblio 1y agoHow much does that thing cost? I don't see a price on the page.
- irusensei 1y agoWhy 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?
- malfist 1y agoBut the ai chatbot popup suggests you can conversationally ask for the specs
- dang 1y agoOne past related thread. Any others? The Asus Ascent GX10 a Nvidia GB10 Mini PC with 128GB of Memory and 200GbE - https://news.ycombinator.com/item?id=43425935 https://news.ycombinator.com/item?id=43425935 - March 2025 (50 comments) Edit: added via wmf's comment below: "DGX Spark has only half the advertised performance" - https://news.ycombinator.com/item?id=45739844 https://news.ycombinator.com/item?id=45739844 - Oct 2025 (24 comments) Nvidia DGX Spark: When benchmark numbers meet production reality - https://news.ycombinator.com/item?id=45713835 https://news.ycombinator.com/item?id=45713835 - Oct 2025 (117 comments) Nvidia DGX Spark and Apple Mac Studio = 4x Faster LLM Inference with EXO 1.0 - https://news.ycombinator.com/item?id=45611912 https://news.ycombinator.com/item?id=45611912 - Oct 2025 (20 comments) Nvidia DGX Spark: great hardware, early days for the ecosystem - https://news.ycombinator.com/item?id=45586776 https://news.ycombinator.com/item?id=45586776 - Oct 2025 (111 comments) NVIDIA DGX Spark In-Depth Review: A New Standard for Local AI Inference - https://news.ycombinator.com/item?id=45575127 https://news.ycombinator.com/item?id=45575127 - Oct 2025 (93 comments) Nvidia DGX Spark - https://news.ycombinator.com/item?id=45008434 https://news.ycombinator.com/item?id=45008434 - Aug 2025 (207 comments) Nvidia DGX Spark - https://news.ycombinator.com/item?id=43409281 https://news.ycombinator.com/item?id=43409281 - March 2025 (10 comments)
- wmf 1y agoIt's the same as DGX Spark so there are several: https://news.ycombinator.com/item?id=45586776 https://news.ycombinator.com/item?id=45586776 https://news.ycombinator.com/item?id=45008434 https://news.ycombinator.com/item?id=45008434 https://news.ycombinator.com/item?id=45713835 https://news.ycombinator.com/item?id=45713835 https://news.ycombinator.com/item?id=45575127 https://news.ycombinator.com/item?id=45575127 https://news.ycombinator.com/item?id=45611912 https://news.ycombinator.com/item?id=45611912 https://news.ycombinator.com/item?id=43409281 https://news.ycombinator.com/item?id=43409281 https://news.ycombinator.com/item?id=45739844 https://news.ycombinator.com/item?id=45739844
- dang 1y agoThanks! Added above.
- nycdatasci 1y agoI ordered one that arrived last week. It seems like a great idea with horrible execution. The UI shows strange glitchy/artifacts occasionally as if there's a hardware failure. To get a sense for use cases, see the playbooks on this website: https://build.nvidia.com/spark https://build.nvidia.com/spark. Regarding limited memory bandwidth: my impression is that this is part of the onramp for the DGX Cloud. Heavy lifting/production workloads will still need to be run in the cloud.
- tcdent 1y agoThe graphics company has given up on graphics.
- lend000 1y agoIs there something similar with twice the memory/bandwidth? That's a use case that I would seriously consider to run any frontier open source model locally, at usable speed. 128GB is almost enough.
- wmf 1y agoMac Studio
- bigyabai 1y agoEven an M3 Ultra won't put up similar GPU compute to a DGX Spark: https://blog.exolabs.net/nvidia-dgx-spark/ https://blog.exolabs.net/nvidia-dgx-spark/ Fill up the memory with a large model, and most of your memory bandwidth will be waiting on compute shaders. Seems like a waste of $5,000 but you do you.
- wmf 1y agoI should also mention that if you want twice the performance of DGX Spark you can buy... two Sparks and link them together.
- sparkler123 1y agoI had one of these on pre-order/reservation from when they announced the DGX Spark and ended up returning it after a couple days. I thought I'd give it a shot, though. The 128GB of unified memory was the big selling point (as are any of the DGX Spark boxes), but the memory bandwidth was very disappointing. Being able to load a 100B+ parameter model was cool in terms of novelty but not particularly great for local inferencing. Also, NVIDIA's software they have you install on another machine to use it is garbage. They tried to make it sort of appliance-y but most people would rather just have SSH work out of the box and can go from there. IMO just totally unnecessary. The software aspect was what put me over the edge. Maybe the gen 2 will be better, but unless you have a really specific use case that this solves well, buy credits or something somewhere else.
- mirekrusin 1y agoI have a weird feeling that "Spark 2" may have an apple logo on it.
- qwertox 1y agoMy hope was to find a system which does ASR, then LLM processing with MCP use and finally TTS: "Put X on my todo list" / "Mark X as done" -> LLM thinks, reads the todo list, edits the todo list, and tells me "I added X to your todo list", ... "Turn all the lights off" -> llm thinks and uses MCP to turn off the lights -> "Lights have been turned off". "Send me an email at 8pm reminding me to do" .... "Email has been scheduled for 8pm" That's all I want. It does not have to be fast, but it must be capable of doing all of that. Oh, and it should be energy efficient. Very important for a 24/7 machine.
- bayindirh 1y agoEnergy efficient LLM inference (for now) is as realistic as existence of perpetual motion.
- mindcrash 1y ago
- mindcrash 1y agoServeTheHome has already benchmarked the DGX Spark architecture against the (very obvious) Ryzen AI Max 395+ with 128G RAM: https://www.servethehome.com/nvidia-dgx-spark-review-the-gb10-machine-is-so-freaking-cool/ https://www.servethehome.com/nvidia-dgx-spark-review-the-gb1... If (and in case of Nvidia that's a big if at the moment) they get their software straight on Linux for once this piece of hardware seems to be something to keep an eye on.
- canucker2016 1y agoGMKtec, maker of the EVO-X2 mini-PC that uses a Ryzen AI Max 395+, posted a blog post with a comparison between the DGX Spark and their EVO-X2 miniPC. from https://www.gmktec.com/blog/evo-x2-vs-nvidia-dgx-spark-redefining-local-ai-performance https://www.gmktec.com/blog/evo-x2-vs-nvidia-dgx-spark-redef... (text taken from https://wccftech.com/forget-nvidia-dgx-spark-amd-strix-halo-mini-pc-delivers-the-same-power-for-half-the-price/ https://wccftech.com/forget-nvidia-dgx-spark-amd-strix-halo-... since the GMKtec table was an image, but wccftech converted to an HTML table - EDIT-reformatted to make table look nicer in monospace font w/o tabs) Test Model Metric EVO – X2 NVIDIA GB10 Winner Llama 3.3 70B Generation Speed (tok/sec) 4.90 4.67 AMD First Token Response Time (s) 0.86 0.53 NVIDIA Qwen3 Coder Generation Speed (tok/sec) 35.13 38.03 NVIDIA First Token Response Time (s) 0.13 0.42 AMD GPT-OSS 20B Generation Speed (tok/sec) 64.69 60.33 AMD First Token Response Time (s) 0.19 0.44 AMD Qwen3 0.6B Model Generation Speed (tok/sec) 163.78 174.29 NVIDIA First Token Response Time (s) 0.02 0.03 AMD
- mindcrash 1y agoAnd additionally Framework apparently benchmarked GPT-OSS 120B (!) on the maxed out 395+ Desktop and reached a 38.0 tok/sec Generation Speed. Given that Nvidia can't even keep up on a 20B model, I assume they can't keep up on the 120B model aswell. https://frame.work/nl/en/desktop?tab=machine-learning https://frame.work/nl/en/desktop?tab=machine-learning So to me the only thing which seems to be interesting about the Spark atm is the ability to daisy link several units together so you can create a InfiniBand-ish network at InfiniBand speeds of Sparks. But overall for just plain development and experimentation, and since I don't work at Big AI, I'm pretty sure I would not purchase Nvidia at the moment.
- amelius 1y ago> and support larger models like LLMs To turn your petaFLOP into petaSLOP.
- NSUserDefaults 1y agoReally looking forward to getting this used for $50 in 6 years just for kicks.
- canucker2016 1y agoDell and Lenovo have product pages for their versions of the DGX Spark. Dell: https://www.dell.com/en-us/shop/desktop-computers/dell-pro-max-with-gb10/spd/dell-pro-max-fcm1253-micro/xcto_fcm1253_usx https://www.dell.com/en-us/shop/desktop-computers/dell-pro-m... - $3,998.99 4TB SSD - $3,699.00 2TB SSD Lenovo: https://www.lenovo.com/us/en/p/workstations/thinkstation-p-series/lenovo-thinkstation-pgx-sff/30kl0003us https://www.lenovo.com/us/en/p/workstations/thinkstation-p-s... - $3,999.00 4TB SSD https://www.lenovo.com/us/en/p/workstations/thinkstation-p-series/lenovo-thinkstation-pgx-sff/30kl0002us https://www.lenovo.com/us/en/p/workstations/thinkstation-p-s... - $3,539.00 1TB SSD
- jdprgm 1y agoMemory bandwidth is a joke. You would think by now somebody would come out with a well balanced machine for inference instead of always handicapping one of the important aspects. Feels like a conspiracy. At least the m5 ultra should finally balance things given the significant improvements to prompt processing in the m5 from what we've seen. Apple has had significantly higher memory bandwidth since the m1 series approaching 5 years old now. Surely an nvidia machine like this could have at bare minimum 500Gb+ if they cared in the slightest about competition.
- frogperson 11mo agoThat is a seriously infuriating webste, at least on mobile anyway.