GPU hosting in Denmark: what it is and how to find the right partner
GPU hosting has become a key technology for businesses working with artificial intelligence, machine learning and generative AI. But what exactly is GPU hosting, when does it make sense over traditional CPU hosting, and how do you find the right partner in Denmark? This guide provides the answers.
What is GPU hosting?
GPU hosting is server hosting using servers equipped with graphics processing units (GPUs) optimised for parallel computing. While a CPU typically has 8–64 cores optimised for sequential tasks, a modern GPU can have thousands of cores designed to perform many calculations simultaneously.
This architecture makes GPUs extremely efficient for tasks such as:
- Training and inference of AI models (LLMs, diffusion models)
- Machine learning and deep learning
- Generative AI (text, images, video)
- Data analysis and scientific computing
- 3D rendering and video processing
CPU vs GPU hosting: what is the difference?
| Factor | CPU Hosting | GPU Hosting |
|---|---|---|
| Cores | 8–128 powerful cores | Thousands of smaller cores |
| Best for | Sequential tasks, web, databases | Parallel computing, AI, ML |
| AI training | Slow (days/weeks) | Fast (hours/days) |
| Price | Low to medium | Medium to high |
| Energy consumption | Low | High |
| Maturity | Very mature technology | Rapidly evolving |
When do you need GPU hosting?
GPU hosting makes sense when your tasks are computationally intensive and can be parallelised. Specific use cases include:
- Running LLMs: Larger models such as DeepSeek, Llama or Mistral need a GPU for acceptable inference speeds
- Image generation: Stable Diffusion and similar models are practically unusable without a GPU
- Model training: Training custom AI models on large datasets can take weeks on a CPU but days or hours on a GPU
- Real-time AI: Applications requiring fast AI inference in real time
- Large-scale NLP: Text analysis and classification across large volumes of data
The hybrid model: CPU + GPU
Most businesses do not need a GPU for everything. A smart approach is to combine CPU and GPU hosting:
- CPU hosting for: Web server, API, database, user interface, logging, backend jobs
- GPU hosting for: AI inference, model training, image generation, demanding ML tasks
This hybrid model is cost-effective because you pay for GPU capacity only when actually using it for demanding AI tasks. The rest of your stack runs affordably and reliably on a CPU.
Benefits of Danish GPU hosting
Choosing a Danish GPU hosting provider instead of international cloud giants has several concrete advantages:
- Low latency: A Danish data centre can provide API response times of 5–15 ms, crucial for real-time AI applications
- GDPR compliance: Data is processed within the EU and does not leave Denmark, simplifying compliance
- Danish support: Direct access to technical support in Danish in your time zone
- Tailored solutions: Local providers can adapt plans to your specific needs
- No vendor lock-in: Avoid dependence on major international cloud providers
Cost-effectiveness: CPU vs GPU
GPU hosting is more expensive than CPU hosting, but it is important to calculate the actual cost per task. A GPU completing an AI inference task ten times faster than a CPU can easily cost less per request, even with a higher hourly rate.
For most SMEs, we recommend starting with a hybrid model: CPU for most tasks and GPU only for parts that truly require it. This keeps costs down while providing the AI capacity you need.
Reliability and security
CPU hosting is a mature technology with well-documented SLAs and operational procedures. GPU hosting is newer, but the best providers now offer comparable reliability.
A good architecture keeps the most critical systems – web server, database and user interface – on stable CPU hosting, while the GPU environment handles demanding AI workloads. If the GPU server briefly goes down, the rest of the platform can still respond to users.
How to choose the right GPU hosting partner
When choosing a GPU hosting partner, consider:
- Technical specifications: Which GPU models are available? NVIDIA A100, H100 or the RTX series?
- Support: Is 24/7 support available with short response times? Can you speak to a Danish technician?
- Flexibility: Can you combine CPU and GPU in the same setup?
- Pricing: Compare the cost per GPU hour and look for hidden fees
- Data centre location: Are the servers in Denmark or the EU?
- References: Does the provider have experience with AI workloads?
GITC as your local GPU hosting partner
At GITC, we offer GPU and CPU hosting in the same setup, so you do not have to juggle multiple suppliers. Run your demanding AI models on dedicated GPU servers while keeping traditional backend services, databases and APIs in the CPU environment.
As a local Danish partner, we can help you design the right architecture for your AI projects, from a simple VPS to complex hybrid solutions with GPU acceleration. Contact us for a no-obligation discussion of your needs.