DGX Spark

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

Benchmarks speak louder than words: Dgx Spark: https://spark-arena.com/leaderboard Framework: https://kyuz0.github.io/amd-strix-halo-toolboxes/ (llamacpp) and https://kyuz0.github.io/amd-strix-halo-vllm-toolboxes/ (vllm) Apple Chips: https://omlx.ai/benchmarks The advantage of VLLM, which is NVIDIA-

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

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.

I've already got an M3 Ultra. I'm going to try this out to get M5 Ultra pp speeds: https://blog.exolabs.net/nvidia-dgx-spark/ Going to start with just one for Minimax 2.7 prefill, but if it works really well I'd consider a second. I somehow expect buying 2 GB10 systems is still going to be cheaper t

Unfortunately, that's about as far as my knowledge goes. I've only been using it for a few weeks, and I was late to the "AI party" in general. I was stubbornly resistant up until about a year ago, then mainly used GitHub Copilot for coding. I've started experimenting with RAG and automations, but I

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

It is a game changer for some local AI workflows, but not because “integrated RAM-VRAM” magically beats every GPU setup. The big deal is the memory pool. A normal PC with a 24GB or 32GB GPU can be very fast, but model size is constrained by VRAM. Once you spill into system RAM, performance usually f

Advanced Marketing Disaster it is. It pains me to see tech youtubers pushing AI Max 395 as a gaming platform. Perhaps they were paid by NVIDIA? I mean, it is made for AI first and foremost, hence the "AI" in its name. It does run video games and it does it pretty well. But for that price, the (gamin