---
title: "Deploy ollama + openweb-ui: run your own open models, own your (free) tokens"
description: "Ollama + OpenWeb-UI + Real, Working, Local Models"
category: "AI/ML"
url: https://railway.com/deploy/ollama-openweb-ui-run-your-own-open-mode
---

# Deploy ollama + openweb-ui: run your own open models, own your (free) tokens

Ollama + OpenWeb-UI + Real, Working, Local Models

**[Deploy ollama + openweb-ui: run your own open models, own your (free) tokens on Railway](https://railway.com/template/ollama-openweb-ui-run-your-own-open-mode)**

Machine-readable deploy manifest (JSON, validated by TemplateCI): https://railway.com/deploy/ollama-openweb-ui-run-your-own-open-mode/manifest.json

- **Creator:** impacte.tech
- **Category:** AI/ML

## Template content

### Open WebUI https://dashboard.snapcraft.io/site_media/appmedia/2024/02/favicon_pUYczil.png

- **Image:** ghcr.io/open-webui/open-webui
- **Public domain:** Yes

### Ollama https://res.cloudinary.com/airplo/image/upload/v1730154334/up9smvbwl2citplphy5a.png

- **Image:** ollama/ollama

## Documentation

# Deploy and Host Ollama + Open WebUI

[![Deploy on Railway](https://railway.com/button.svg)](https://railway.com/deploy/impacte-ollama-webui)

Run your own private AI chat — **Ollama** serving 100+ open models (Llama, Qwen, Gemma, Mistral, DeepSeek, Phi and more) with **Open WebUI** on top: a polished, self-hosted ChatGPT-style interface. No API keys, no rate limits, no per-token bills — your prompts never leave your Railway instance.

> 🎯 **Stop renting tokens. Own them.** With closed-model APIs you pay for every token, forever. Here, tokens are unlimited and free — you only pay for infrastructure.

## 🚀 Getting Started with Ollama + Open WebUI on Railway | Deployment Guide

Once your Railway deploy is live, open your Open WebUI URL — the first account you create automatically becomes the admin.

### Step 1: Create Your Admin Account

Open your service URL and sign up. The first registered user gets full admin rights over models, users, and settings.

### Step 2: Pull Your First Model

Go to **Admin Panel → Settings → Models → Pull a model** and pull any model from ollama.com by name, for example `llama3.1:8b` or `qwen2.5:7b`. Models download straight to your persistent volume, so they survive redeploys. You can also pull curated, community-tuned configs from [ollama.com/oamazonasgabriel](https://ollama.com/oamazonasgabriel) — optimized for consumer-hardware-class resources.

### Step 3: Chat

Pick the model in the top-left dropdown and start chatting. Switch models mid-conversation, run side-by-side comparisons, or attach documents for RAG-powered answers.

### Step 4: Connect Your Apps (Optional)

Generate an API key in **Settings → Account → API Keys** and point any OpenAI-compatible tool at your own endpoint. Your apps get an AI backend with zero per-token billing.

## About Hosting Ollama + Open WebUI 📖

This template deploys a production-ready, two-service stack with persistent storage:

- 🦙 **Ollama** — the model runtime. Pulls and serves open models, exposes an OpenAI-compatible API. Kept **private** (no public domain) and wired to WebUI over Railway private networking.
- 💬 **Open WebUI** — the ChatGPT-style interface. Multi-user auth, chat history, markdown + code highlighting, voice input, document uploads (RAG), and web search. This is the only public-facing service.
- 💾 **Two persistent volumes** — one for pulled models (`/root/.ollama`), one for users, chats, and uploads (`/app/backend/data`). Both survive redeploys and updates.

Your models and conversations are 100% yours: nothing is sent to third parties, and there are no token meters running.

## Why Deploy Ollama + Open WebUI on Railway ✅

One-click deploy with zero server configuration:

- 🟢 No Docker, driver, or CUDA setup — Railway handles it all
- 💾 Persistent volumes keep models, chats, and accounts across deploys
- 🔐 Private networking between services — Ollama is never exposed publicly
- 📉 Scale down when idle and pay pennies; scale up for heavy sessions
- 🧩 GPU instances available (plan/region dependent) for 10–30× faster inference
- 🌐 Browser-based everything — pull models and manage users without SSH
- 🔄 Redeploy to update images — models and data persist

## Common Use Cases 💡

- **Private ChatGPT alternative** — personal or team AI chat with zero data leaving your server
- **Free-token API backend** — replace per-token API bills with an OpenAI-compatible endpoint you own
- **Document intelligence** — upload PDFs and docs, chat with them via built-in RAG
- **Team AI workspace** — multi-user accounts, shared prompts, per-user history
- **Open-model experimentation** — benchmark models, tune system prompts, compare answers side-by-side
- **Sovereign AI** — run open-weight models (Llama, Qwen, Gemma, DeepSeek, Mistral) on infrastructure you control

## Dependencies for Ollama + Open WebUI 📦

- **Ollama** — official `ollama/ollama` image, model storage persisted at `/root/.ollama`
- **Open WebUI** — official `ghcr.io/open-webui/open-webui` image, data persisted at `/app/backend/data`
- **Railway private networking** — WebUI reaches Ollama via `OLLAMA_BASE_URL=http://ollama:11434`

### Dependencies for
### Deployment Dependencies

- **Ollama:** [ollama/ollama](https://github.com/ollama/ollama) — [Model library](https://ollama.com/library) — [Curated configs](https://ollama.com/oamazonasgabriel)
- **Open WebUI:** [open-webui/open-webui](https://github.com/open-webui/open-webui) — [Docs](https://docs.openwebui.com)

## 🖥️ Minimum Hardware Requirements for Ollama + Open WebUI

| Model class | Examples | Min RAM | Experience |
|---|---|---|---|
| 1–4B | Llama 3.2 3B, Gemma 2 2B, Phi-3.5 | 4–8 GB | Snappy on CPU |
| 7–9B | Llama 3.1 8B, Qwen 2.5 7B, Mistral 7B | 8–16 GB | Good on CPU, fast on GPU |
| 13–14B | Qwen 2.5 14B | 16 GB+ | Usable on CPU |
| 30B+ | Qwen 2.5 32B, DeepSeek-R1 32B | 32 GB+ | GPU recommended |
| 70B | Llama 3.3 70B | 48–64 GB+ | GPU strongly recommended |

💡 Start with a 7–8B model — the sweet spot for quality vs. cost. Attach a Railway GPU where available for serious inference speed.

## 💰 Own Your (Free) Tokens — The Economics

| | Closed APIs (per-token) | **This template** |
|---|---|---|
| Token costs | Every request bills | **$0 — unlimited** |
| Heavy month (10M tokens) | $30–150+ | Same infra price |
| Privacy | Prompts leave your control | Prompts stay on your instance |
| Model freedom | Vendor's catalog | 100+ open models, swap anytime |

**Reality check:** you pay for RAM/CPU while running, not tokens. An always-on 8 GB instance is ~$80/mo — heavy API users break even fast. Everyone else can **scale down when idle**: models reload from the volume in seconds on demand, so light usage costs literal pennies.

## 🐳 Self-Hosting Ollama + Open WebUI Outside Railway

Prefer your own hardware? The same stack runs anywhere Docker runs:

```bash
# 1) Ollama with persistent model storage
docker run -d --name ollama -p 11434:11434 -v ollama:/root/.ollama ollama/ollama

# 2) Open WebUI, pointed at your local Ollama
docker run -d --name open-webui -p 3000:8080 \
  -e OLLAMA_BASE_URL=http://host.docker.internal:11434 \
  --add-host=host.docker.internal:host-gateway \
  ghcr.io/open-webui/open-webui:main
```

Open `http://localhost:3000`, create your admin account, and pull models as usual.

## ❓ FAQ

**How do I add models?** Admin Panel → Settings → Models → pull by name (`qwen2.5:7b`, `gemma2:9b`, `deepseek-r1:8b`…). Models persist across redeploys on the volume.

**Are my chats and prompts private?** Yes — everything stays on your Railway instance and volumes. Nothing is sent to third parties.

**Can I use my existing OpenAI tools and SDKs?** Yes — Open WebUI exposes an OpenAI-compatible API with keys you control. Point any OpenAI client at it.

**A model feels slow on CPU.** Use a smaller or quantized model (e.g. `:4b` variants), or deploy in a GPU-enabled region and attach a GPU.

**How do I update the stack?** Hit redeploy — both images update, and your models, chats, and accounts persist on the volumes.

**Can multiple people use it?** Yes — every user gets their own account, history, and settings. Admins manage users and default models.


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- [Hermes Agent | OpenClaw Alternative with Dashboard](https://railway.com/deploy/hermes-agent-or-openclaw-alternative-wit) — Self-Hosted Hermes AI Agent for Telegram, Discord & Slack

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