How much does an AI server for an SME cost in 2026?
A clear breakdown of the real cost of a local AI rig in 2026: hardware, software, electricity and support, with three priced tiers and a cloud API comparison.
The honest answer is not a single price. In 2026, a useful local AI server for an SME usually lands between EUR 5,000 and EUR 25,000 depending on the model size, the number of concurrent users and the level of support you need.
What you are really paying for
A local AI server is not just a GPU in a tower. The GPU decides which models fit, but the rest of the platform decides whether the machine is reliable, quiet and maintainable.
| GPU(s) | 55-70% | VRAM decides which LLMs can run. |
| CPU, RAM, NVMe | 15-20% | Needed for RAG, loading checkpoints and serving users. |
| Power, case, cooling | 8-12% | Required for stable dual-GPU builds. |
| Software and integration | 5-10% | Drivers, Ollama, vLLM, llama.cpp, Open WebUI and RAG setup. |
| Warranty and support | included | Parts and labour, not a hidden add-on. |
The three realistic tiers
- Starter around EUR 4,990 HT: one RTX 5090, good for 7B to 32B models and solo experimentation.
- Pro around EUR 11,990 HT: two RTX 5090s, the sweet spot for Llama 70B Q5, agencies and small teams.
- Enterprise from EUR 25,990 HT: pro GPUs, more VRAM, RAG kit, support and compliance-oriented deployment.
What the cloud comparison hides
A EUR 600 monthly API bill looks comfortable until agents start calling the model all day, long-context prompts are billed every time, and sensitive data requires enterprise contracts.
For a small legal or consulting team doing hundreds of RAG requests per day, a Pro rig can cost two to three times less than equivalent API usage over three years.
When buying makes sense
- Your API bill has stayed above EUR 500 per month for several months.
- You work with sensitive legal, medical, HR or R&D data.
- You are moving from chat experiments to agents or batch workflows.
- You want a development and test environment without a meter running on every call.
If you describe your use case in five lines, LocalIA can size the right tier and give you a firm quote instead of a vague parts list.
Open the calculator / request a quote with your target model, users and constraints.