DGX Spark

nvidia is being affected by the dram most likely. they dont make parts in house they actually buy them. if its short everywhere then nvidia cant buy their parts to make their new stuff they might sell the shovels but they are starting to get expensive to make. meanwhile apple jumped in to make custo

https://www.nvidia.com/en-us/products/workstations/dgx-spark/ it's $4,000. in my pc i have a 4070. The DGX spark is 30x more powerful for AI workloads

NVIDIA did - they call it the DGX Spark. I have one. 128 GB of LPDDR5X memory to the Grace Blackwell chip. $3999 retail. Apple could smash this thing to bits with an M6 with a bajillion neural cores and the same RAM. They could price it at $1999 and take the whole market. They’re already doing it wi

You wont buy it https://www.microcenter.com/product/699008/nvidia-dgx-spark

I went through the gauntlet. Started with an rtx 3090 + 128 gb ddr4 (sold) -> rtx 5090 + 128 gb ddr5 (kept) -> halo strix 395+ (returned) -> dgx spark (returned) -> m4 max 128 gb (kept) -> m3 ultra 256 gb (kept) If your main focus is coding there is nothing else than the m3 ultra or m4 max. The m5 m

2x Asus Ascent GX10 (same hardware as Nvidia DGX Spark - cost me €5300 total excl VAT), with official checkpoint from DeepSeek https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash-DSpark Runs at ~2K pp and 50-60 tg ; which is around half of API speed, but local! It doesn't make financial sense given

Welcome to the club. The harder thing to resist is buying a second one. forums.developer.nvidia.com/c/accelerated-computing/dgx-spark-gb10/dgx-spark-gb10/721 awesome resource Current top-pick for single spark: Qwen 3.5 122B-A10B, Qwen 3.6 27B (with MTP) or even the 35B-A3B if speed matters more. htt

Depends on what you call "professional grade" The 400 billion model you just need enough unified ram or vram and some decent flops and bandwith. e.g. you can run the 671b deepseek model at 18 tok/sec on a mac studio m3 ultra with 512 gb of unified ram. Price is around 10k I think. No need for a gian

Google One Pro: Storage, Gemini, etc.. Internet Home workers My servers & my ❤️ NVIDIA DGX Spark.

Project DIGITS / DGX Spark only ever made sense as a pipe-cleaner for a chip with much broader ambitions. The desktop mini PC AI workstation market just isn't big enough to justify designing this much custom silicon. But releasing a developer-oriented Linux desktop first while working on the Windows