Share a Local LLM with Multiple Users Using Ollama

8/12/2025

So You Want to Run a Local LLM for Multiple Users with Ollama? Here's How.

Hey everyone, let's talk about something that’s becoming a SUPER common question: how do you actually share your local LLM with a team? You've got Ollama running smoothly on a machine, you're chatting with Llama 3 or Mistral, & it's awesome. But now, your colleagues want in on the action. How do you go from a one-person setup to a multi-user powerhouse without everything grinding to a halt?

Honestly, it's a bit of a journey, but it's totally doable. It’s not as simple as just passing around an IP address (though that's part of it). You need to think about access, performance, & user experience. The good news is, the tools to make this happen are getting better every day.

I've been down this rabbit hole, and I'm here to share what I've learned. We're going to go deep on how to set up Ollama so multiple people can use it at the same time. We'll cover everything from the basic network setup to performance tuning & even deploying a slick web interface so non-technical users can join the fun.

Why Even Bother Running a Local LLM for Your Team?

First off, why go through this trouble? Why not just use a cloud-based service? There are some pretty compelling reasons to keep things in-house.

Privacy & Data Security: This is the big one. When you run an LLM locally, your data never leaves your infrastructure. For businesses dealing with sensitive customer information, proprietary code, or confidential documents, this is non-negotiable.
Cost Control: Cloud LLM APIs can get expensive, FAST. The costs are often unpredictable & based on usage. A local setup is a fixed cost—you buy the hardware, & that's it. No per-token fees.
Customization & Control: Running your own LLM means you have total control. You can fine-tune models on your own data, experiment with different open-source models, & customize the experience to your heart's content.
Offline Access: Once your local server is set up, it can run completely offline. This is great for environments with limited or no internet access.
Reduced Latency: With the LLM running on your local network, you can get much faster response times compared to making API calls over the internet.

The Core Concept: Exposing Ollama to Your Network

Here's the thing you need to understand right away: Ollama itself doesn't have a built-in user management system. It's designed to be a simple, powerful tool for running LLMs locally. By default, it runs on

localhost

, meaning it only listens for requests from the same machine it's installed on.

To share it with other users on your network, you need to configure it to listen on all network interfaces. This is done by setting an environment variable called

OLLAMA_HOST

0.0.0.0

. This tells Ollama to accept connections from any IP address on your network, not just

localhost

How you set this environment variable depends on your operating system:

On Linux (with systemd):

This is probably the most common setup for a shared server.

Open the Ollama service file for editing: