ATAGB10-9000

Why not buy a Nvidia DGX Spark? This is the perfect AI workstation and includes a library of tools for AI work. You can also look at other DGX OS machines like HP ZGX, Gigabyte AI Top Atom, Lenovo, Dell, Asus. These are in your budget and you can also link them for more power down the road. I person

TLDR: Overview of NVIDIA DGX Spark partner variants available in summer 2026. What is DGX Spark? A compact personal AI supercomputer powered by the GB10 Grace Blackwell Superchip.Key shared specs across all variants: Up to 1 petaFLOP FP4 AI performance 128 GB unified LPDDR5x memory Can run models up

Sharing my secret sauce - spent nearly 2 days battling demons, running NVIDIA NIM, generic vllms, builts some but all to no avail. It worked under custom-built Llama.CPP at about 45-50 tps and now about 65-70 on this specific vLLM image. This is on GB10 box( Gigabyte-clone of Spark): sudo docker run

I don't think this is an optimized solution for your business because it's very expensive compared to the alternatives. Each 6000 Blackwell chip is $12,700 - $14,000 + large power supply and running it will draw a lot of power. My personal setup is a Gigabyte AI Top Atom. 128 GB unified memory, very

I'm using mg Gigabyte AI Top Atom with Qwen3.6-35B + 262k conext window and it's fast and never gives me any issues.

Even then the ai performance with the cpu isn't as good as you may expect. You'd have to run with turboquant transformer and preferably do so in linux to uncap the windows cpu ram limit. Even then it would be incredibly slow for most semi intelligent model and pretty much useless for coding. Amd's s

Yo, new to the sub but I have so far tried multiple things from self hosting on my machine, self hosting on a dedicated machine, self hosting on a GIGABYTE AI TOP ATOM, paying for Anthropic, paying for OpenAI, Azure Foundry etc and here is my takeaway. Anthropic via Claud Code so far has given me th