DGX Spark

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

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

I’ve got a Strix Halo and 2x GB10 (Nvidia DGX Spark, but the Asus version). For pure AI workloads, I’d go with the GB10. For example, on GPT-OSS-120B I’m hitting ~6000 pp and 50–60 t/s with vLLM, and I can easily serve 3 or 4 parallel requests while still outperforming my Strix Halo, which struggles

Firstly you should understand that the Ryzen AI Max+ 395 chip is not intended to be an all-purpose AI chip. It comes with a lot of memory, but does not support CUDA, does not have a lot of compute, and most importantly does not have a lot of memory bandwidth. Not supporting CUDA means the options fo

It might not have lived up to the hype but it gets the job done. People also underestimate how much noise, power and heat a system with duel full height graphic cards put out. The Mac Studio and DGX Sparks give you very capable systems in a small convenient package. AMD Strix Halo is also an option

I've ordered the Asus GX10 for running Qwen3.5-122B-A10B Q4 (we'll see which version of Q4 is the best - native MXFP4 support by the GB10 chip seems interesting). My goal: cancel all AI subs (currently Claude Max x5 and ChatGPT Plus) It's not just a pipe dream, I'll do everything to achieve it. Cont

As someone who runs local models on a Mac Studio and Nvidia DGX Spark you aren’t running anything close to foundation models from a year ago on a Mac Mini; especially one with 32GB of memory. You need something with a minimum of 64GB to fit a large enough context window and run something like Qwen 3

Ćao. Trenutno budget rešenje je da plaćaš pretplatu jer je alternativa skupa ali i zabavna. Lokalni modeli postaju sve bolji (često tako što se "krišom" treniraju pomoću podataka koji se dobijaju upravo od komercijalnih providera poput OpenAI, Anthropic itd.), i između ostalog baš zbog toga npr. 9B

If you want long context processing, Mac is not a good choice. Actually, the worst among other choices, because of extremely slow reading speed. Note that this is different from the TG speed you mentioned. But for your use case, it is far more important, as others have mentioned. So Prefill speed (P

It competes with things like Nvidia DGX Spark, which has 273 GBs (and a lot less cores). It's not a bad product, the worst thing is that AMD's ecosystem is not as large as Nvidia's.