AI & machine learning servers Self-host any AI tool — from €3.90/mo
GPU servers · Unlimited traffic · 120+ locations

It depends on your use case. For running chatbots and lightweight AI assistants (like OpenClaw), no GPU is needed — a VPS or Cloud server is enough. For running language models locally (Ollama, LocalAI with 7B+ models), 16 GB RAM on CPU works but slowly; a GPU gives 10x speed. For image generation (Stable Diffusion, ComfyUI) and production LLM serving (vLLM), a GPU is effectively required.

For most users: an RTX 4090 with 24 GB VRAM is the best balance of cost and capability. It runs all 7–13B models at full speed, handles SDXL and Flux for image generation, and covers most production inference workloads. For 70B models or enterprise throughput, an A100 with 80 GB VRAM is the standard.

OpenAI charges per 1M tokens — costs scale with usage. A self-hosted server costs the same regardless of how much you use it. Heavy users often break even within the first month. You also get full privacy, no rate limits, and the ability to use any open-source model.

Yes, within the limits of your VRAM and RAM. An RTX 4090 with 24 GB VRAM can run two 7B models simultaneously, or one 13B model with room for other processes. An A100 with 80 GB VRAM can hold multiple large models in memory at once.

Yes, for several reasons: downloading models (2–80 GB each), streaming generated text back to clients, serving image generation outputs, and handling API traffic from multiple users. Bandwidth caps add unpredictable costs and can throttle your throughput. All Dedimax plans include unlimited traffic.

Yes. Ollama and LocalAI both support CPU-only mode, which works for development and low-throughput use. When you're ready, switch to a dedicated GPU server — the software setup is the same, and GPU acceleration is detected automatically.