The price on the card is the price on the invoice.

Because you're renting the actual machine, not a slice of one with a hyperscaler's margin stacked on top. There's no egress billing, no per-hour meter, no support tier to upgrade into. One flat monthly number for the whole box, and the GPU is yours alone for the month.

Nothing you'd notice. The facility runs behind a battery bank with a solar array feeding it, so a utility cut is a transfer, not an interruption — the batteries carry the load and the panels recharge them. Network is the same story: two independent fiber carriers, not two drops from one provider, so a single carrier's outage doesn't take the rack with it. This is the reason the business exists.

No. Every plan is a dedicated card in a dedicated box. You get the full VRAM, the full clock, and root. Nothing is virtualised, oversold, or time-sliced, so throughput doesn't move around based on who else is on the machine.

Rough rule for inference: VRAM in GB should be about double the parameter count in billions at fp16, or roughly equal to it at fp8. A 32B fits an RTX 5090 at fp8; a 70B wants the 96 GB RTX PRO 6000 to stay on one card. Tell us the model and the context length you're targeting and we'll tell you honestly which box to take — including when the cheaper one is enough.

Full root on bare metal, and yes to Docker. Ubuntu 24.04 by default with the driver stack already in place — CUDA on the NVIDIA boxes, ROCm on the AMD ones — plus the container toolkit. vLLM, Ollama, llama.cpp, ComfyUI, PyTorch and TensorFlow all run as they do on any other machine you own. Bring your own ISO if you'd rather.

Usually, but check first — this is the one thing worth five minutes before you order. PyTorch, vLLM, llama.cpp and Ollama all have working ROCm support, and for straightforward LLM inference the AMD boxes are the cheapest VRAM we rent. Where it gets thin is custom CUDA kernels, some quantisation libraries, and anything depending on a niche NVIDIA-only package. Tell us what you're running and we'll give you a straight answer rather than a maybe — and if the answer is that you need CUDA, we'll point you at the NVIDIA plans instead.

In-stock configurations are typically handed over the same day — you get an IP, root credentials, and a working driver stack. Custom builds depend on parts and we'll give you a real date rather than a hopeful one.

Not today. Hourly billing means keeping cards idle between customers, and the cost of that idle time gets priced back into every hour you do use. Flat monthly is how the rate stays where it is. If your workload is genuinely bursty, a hyperscaler's spot market will beat us and we'll say so.

Month to month. No setup fee, no minimum term, cancel with 30 days' notice. Invoiced monthly by card or ACH.

The person who built the rack. There's no ticket tier and no offshore first line — you get a direct line to someone who can actually get hands on the hardware. That's a genuine advantage of being small, and it stops being true if we ever get big enough to need a call centre.