---
title: "GPU servers in Europe · Rent dedicated GPUs by the hour"
description: "Rent dedicated GPU servers in European data centres to fine-tune models, serve your own weights or run batch jobs. Compare price, region and stock first."
canonical: "https://inference.eu/gpus/"
language: "en"
---

GPU servers in the EU

# Rent dedicated GPU servers in European data centres for your own AI workloads

When a shared API isn't enough, rent a GPU server of your own in an EU region. Fine-tune a model, serve your own weights or run a batch job, and stop paying when it's done.

[Contact sales](https://inference.eu/contact/)[How it works](#features)

## How it works

-   ### Compare offers before you rent

    See GPU type, price per hour, region and availability side by side.

-   ### EU regions only

    Filter to data centres in the European Union so the workload and its data stay there.

-   ### Billed by the hour

    Start a server for a job and stop it when you're done. No long contract.

-   ### Dedicated, not shared

    The GPUs in a server you rent are yours for as long as you rent it, so no other customer's job competes for them.

-   ### Your data stays on your server

    Training data and weights stay on hardware only you use. Nothing you run is used to train anyone else's model.

-   ### Billed in euros

    Hourly usage appears on the same euro invoice as the rest of the platform.

## What teams run on them

-   ### Fine-tuning

    Adapt an open model to your own data on hardware only you use.

-   ### Serving your own model

    Run your own weights behind an endpoint, for latency or privacy you control.

-   ### Batch jobs

    Embed a document archive, transcribe audio or label data overnight.

## GPUs: common questions

The questions buyers, developers and legal teams ask us most. Something missing? Ask us directly.

The comparison shows every current offer across European data centres, with its GPU type, memory, price per hour and region. Stock changes by region and by day, so filter by the memory your model needs and pick the offer that fits your workload and budget.

Every offer shows its region before you rent. Filter to data centres in the European Union and the workload and its data stay there. The subprocessors involved are listed with your data processing agreement under GDPR Article 28.

Yes. Bring your weights, or start from an open model, and serve it on a server you rent. You choose the inference software and expose the model behind an endpoint, so latency, versions and access stay under your control.

No. Servers are billed by the hour and you can stop one at any time. That suits jobs with a clear end, such as a fine-tuning run or an overnight batch, as well as testing a setup before you commit to longer use.

Use the shared API when an available model does the job, because it's simpler and you pay per token. Rent a GPU server when you need your own weights, a fine-tune, a model the API doesn't serve, steady high volume or full control over the software stack.

Yes. Rent a server with enough GPU memory for the model size, load an open-weight base model and train on your data. The data and the resulting weights stay on hardware only you use, in the region you chose.

No. What you run on a rented server is yours. We never use your data, prompts or weights to train any model, and this commitment is part of the data processing agreement under GDPR Article 28 that you sign with us.

You pay for each hour a server runs, and the charge appears on one invoice in euros together with any API usage. The price per hour is shown on each offer before you start, so there are no surprises at the end of the month.

Yes. Start a server, run the job and stop the server when it finishes, paying only for the hours in between. Typical batch jobs are embedding a document archive, transcribing a backlog of recordings or labelling a dataset for training.

Yes. If an open-weight model on the shared API turns out to fit your needs, point your code at the API and stop the server. Both run on the same account and the same invoice, so moving between them needs no new contract.

Teams that need their own hardware, such as machine learning engineers fine-tuning models, product teams serving a custom model and data teams with large batch jobs. If you only need a model behind an API, the shared Models API is the simpler choice.

[Ask a question](https://inference.eu/contact/)

## Move your AI workloads to EU infrastructure

Tell us which models you use and roughly how much traffic you have. We reply within one working day with pricing and next steps.

-   Reply within one working day
-   Pricing for your volume
-   DPA ready to sign