What is private LLM hosting?
Private LLM hosting means running open large language models on dedicated hardware that you control, instead of sending prompts to a public API. For many businesses, that difference is the whole point.
The core idea
A public AI API is convenient, but every prompt and document leaves your environment. Private LLM hosting flips that: the model runs on a server that is yours alone, so prompts, embeddings and model weights stay inside your own infrastructure.
In practice this is a dedicated GPU server running an open-weight model through a runtime such as vLLM or Ollama, reachable only by your applications.
Why teams choose it
- Sensitive or regulated data must not leave the company.
- Predictable cost instead of per-token billing that scales with usage.
- Full control over the model version, configuration and uptime.
- No dependency on a third party changing or deprecating a model.
What it runs on
The hardware is a single-tenant GPU server, sized to the models you intend to serve. GPU count and VRAM are matched to model size, with fast NVMe storage and a 1 to 100GbE uplink depending on traffic.
You keep full control. We can pre-install the OS, drivers and runtime on request, but after handover the model stack is entirely yours to manage over IPMI and root access.
Is it for you?
If you are experimenting, a public API is fine. Once a workload becomes sensitive, high-volume or business-critical, a private server usually wins on cost, control and privacy.
In short: Private LLM hosting puts open models on dedicated hardware you control, keeping data in-house. Request a custom quote