Got GPUs in your rack, datacenter or colocation? Connect them to HostYourAI. Run compliant AI on them with our full management layer, or supply capacity to the European pool and earn from hardware that sits idle today.
Early access: we onboard the first pools personally.
You already have GPUs, on-prem or in colocation. We put the HostYourAI layer on top: vLLM deployments, the model garden, and an OpenAI- and Anthropic-compatible API on your own hardware.
Do your GPUs sit idle part of the day? Connect them to the shared Router and earn per GPU-hour consumed. We bring the workloads, the billing and the customers. You bring power, uptime and an EU address.
The same path for both tracks. Vetting and benchmarking take the most time, the technical part is an afternoon.
GPU types, VRAM, network and location. A short email is enough for a first answer.
We verify the hardware is in the EU and yours, and run a benchmark on your machines.
vLLM plus a secured agent, rolled out via Docker. All traffic is encrypted end-to-end.
Your pool shows up in your own dashboard or in the Router. From then on you see usage, uptime and the monthly settlement.
Not sure your setup qualifies? Email your specs and you will get an honest answer.
We are in early access and scope this per project: the price of the management layer depends on the number of GPUs and what you want to run on them. There is deliberately no fixed price list yet. Book a call and you will get a concrete proposal.
You are compensated per GPU-hour actually consumed by customers. The rate depends on the GPU class and the uptime you can guarantee, and is agreed per partner. Settlement is transparent and monthly.
With your own pool: yes. Prompts and responses are processed on your GPUs and never leave your network. We do not log prompt or response content by default, only usage metadata for the dashboard. See our security page for details.
NVIDIA cards with 24 GB VRAM or more, located in the EU, with a stable connection. Older or smaller cards are not rejected automatically, but the benchmark decides whether they fit the pool. Email your specs if in doubt.
That is exactly what we are building towards: your own workloads first, and idle capacity earning in the pool. During early access we assess per partner what is already possible.
The technical part is not the bottleneck: with Docker access the runtime is up in an afternoon. Vetting and benchmarking take the most time. Think days to weeks, not months.
One email with your GPU types and location is enough for a first answer, usually within the week.