Notes from taking third spot at the Dell x NVIDIA AI Hackathon

I signed up for the Dell x NVIDIA local AI hackathon last Sunday. One day, forty Dell Pro Max boxes with GB10 chips on the tables, and a hard rule: build something that runs entirely on the box. No cloud APIs. No pre-built agents.

We took the “no pre-built” rule further than we needed to. We didn’t even pre-discuss ideas. We wanted to see if a team that had never worked together could brainstorm cold on the day and still ship something worth demoing. That was the whole exercise.

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Setup ate the first two hours

The event was well organized. My one complaint: not enough coffee. There were energy drinks, and we made do, but coffee is coffee.

The bigger problem was the Wi-Fi. Getting the GB10 online and pulling the last few dependencies. Anything that touched the network cost us 30 to 60 minutes we didn’t have. As per instructions, we’d already brought the models pre-loaded on a pendrive. Brian had brought a portable network switch, and the moment he plugged it in, connections were working fine.

I’ve been running local models for a while, so I had the weights on me and the stack scripted in my vLLM repo. Once the box was online, I brought up Qwen3.6-27B (27B dense) behind a LiteLLM gateway and exposed it on the local network so the whole team could hit it. That gave us a working local inference endpoint about a third of the way into the day.

I’ve documented my setup previously here:

The hardware provided — GB10 boxes, monitors, keyboards, mice — was generous. But the peripherals were Bluetooth. Half of them didn’t pair cleanly. More on that at the end.

Finding a problem worth solving locally

We spent the next stretch brainstorming. Four people who had never built AI solutions together, all coming from different domains, all with their own pet ideas. It took a while to converge, and honestly I underestimated how long that would take.

We put two constraints on the wall before we picked…