DGX Spark

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

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

I can't tell if people are serious when they defend the reason for the DGX Spark existing. I honestly started laughing thinking you were joking about tough workloads training small models til you started comparing and adding defenses and I figured you are being serious... I'm not trying to be disres

I'd love to show the entire desk, speakers, etc. but I'm afraid everything surrounding is a bit of a mess 'PC' is an Nvidia DGX Spark. Needed something with plenty of memory, strong CUDA support, & something small I can take with me for travel. It is a hair better than a 9950x in CPU performance & a

Exactly. Steam on the Snapdragon 8 Elite gen 5 will be 30-75% faster than the Steam Frame. Duct tape the fucker to your head. Easy. I'm more excited for Steam on the next Nvidia-ARM device (like the DGX Spark). If they launched a high-end one that could run steam, they would clean up. Steam should p

Have you looked at the NVIDIA DGX Spark? 128GB VRAM, GB10 GPU complete system for around $4000 and zero supply issues. I have one and its great.

DGX is not for anything other than AI, and big models at that. It's a 5070ti speed wise. The 5070ti has 896GB/s memory bandwidth while the DGX Spark and the Minisforum S1 Max have 256GB/s memory bandwidth so it's literally 3.5x slower. You don't buy it for that. You buy it to run 200b parameter mode

I ran some benchmarks on Ollama with llama3.2:1b and it was ~ 3.5x faster on Nvidia than on AMD. I'm usually using my dgx spark for the LLM so I didn't benchmark a lot of models. For me, being able to run cuda-enabled things, faster local LLM, and gsync to my external monitor made it worthwhile. If

• you are looking to save 12k a year here, perhaps the hardware budget you set for yourself is too small?- since you don't mind speed (which makes sense. if you are spending 1000s on copilot then your prompts probably take hours), then VRAM is king. Optimize for that?- For ~1500 IMO the best bang for

Kommt drauf an für wie viele Leute man was genau bereitstellen will. Die kleinen DGX Spark Boxen mit NVIDIA Blackwell mit unified memory haben den Markt ziemlich umgekrempelt. Für ~10k kriegst du 3x ASUS GX10, die kann man mit QSFP Kabel zusammen hängen für insgesamt 384 GB VRAM. Da passt die grosse