Server for Ollama
A local inference stack for quickly running open models and enterprise AI applications.
What it is
Ollama is a simple runtime for open-weight models. It shines in prototyping and small production scenarios: fast start, a single interface, a broad model library. We size the server so Ollama runs reliably and does not hit memory limits as load grows.
When it fits
- Quick start with local AI
- Individual development and experiments
- Coding assistant for a team
- A small AI service with moderate load
What to keep in mind
- For high concurrency and production throughput, vLLM is better
- Efficiency depends heavily on quantisation
- Not every model is in the Ollama registry — some need manual conversion
- Ollama’s monitoring and logging are minimal — an external layer is often needed
Frequent questions
Ollama or vLLM for production?+
For high-load production, vLLM. Ollama remains optimal for quick start, development and light workloads. Using both is often right: Ollama for development, vLLM for production.
Can several models run at once?+
Yes, given enough VRAM. Ollama unloads models that are not in use, so several can coexist on one server.
Is Ollama compatible with the OpenAI API?+
Yes. Ollama exposes an OpenAI-compatible API, so existing applications can be pointed at it without rework.
Let’s discuss your task
Tell us what the AI contour needs to solve — we will match the configuration, infrastructure and next step.