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

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

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

Post on over to r/localllama or check out the wiki there for setups. DGX sparks are not an inference powerhouse for the $$$$ you’d spend. It’s not an enterprise grade system for 1500 users either. It’s for local, personal prototyping on the same environment as you’d deploy when you deploy to a large

Those models perform a lot worse than the API you'd spend 100k/year on. And the inference speed is a single digit percent of it as well, uselessly slow. If you consider those aspects this is not a great purchase. Honestly better off just getting Nvidia's 100GB workstation GPUs for 7k a piece. Their

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

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

The "AMD effect" is happening when it comes to Nvidia DGX Spark. The legendary developer John Carmack put DGX Spark through its paces and he came away disappointed with the product: DGX Spark appears to be maxing out at only 100 watts power draw, less than half of the rated 240 watts, and it only se

I own a M4 Max MacBook Pro 128GB RAM with a 4TB SSD. I recently bought a DGX Spark. Then returned it a few weeks later. I thought I was buying a smaller, slower Blackwell AI datacenter for my home lab when I bought a Spark. I was wrong. It’s a poorly-supported ARM knockoff of the sm120 ecosystem cal