🔐🦙Private & local Ollama self-hosted + dynamic LLM router
Who is this for? This workflow template is designed for AI enthusiasts, developers, and privacy-conscious users who want to leverage the power of local large language models (LLMs) without sending data to external services. It's particularly valuable for those running Ollama locally who want intelligent routing between different specialized models. What problem is this workflow solving? When working with multiple local LLMs, each with different strengths and capabilities, it can be challenging t
At a glance
🔐🦙Private & local Ollama self-hosted + dynamic LLM router is a ready-made n8n workflow you import as a workflow JSON file — no build required. It connects UNSUPPORTED_SLUG_FORMAT. It's free to download. Follow the 5-step import below to go live in minutes.
- Platform
- n8n
- Connects
- UNSUPPORTED_SLUG_FORMAT
- Modules
- 7
- Price
- Free
- Version
- v1.0

About this workflow
Who is this for? This workflow template is designed for AI enthusiasts, developers, and privacy-conscious users who want to leverage the power of local large language models (LLMs) without sending data to external services. It's particularly valuable for those running Ollama locally who want intelligent routing between different specialized models. What problem is this workflow solving? When working with multiple local LLMs, each with different strengths and capabilities, it can be challenging to manually select the right model for each specific task. This workflow automatically analyzes user prompts and routes them to the most appropriate specialized Ollama model, ensuring optimal performance without requiring technical knowledge from the end user. What this workflow does This intelligent router: - Analyzes incoming user prompts to determine the nature of the request - Automatically selects the optimal Ollama model from your local collection based on task requirements - Routes requests between specialized models for different tasks: - Text-only models (qwq, llama3.2, phi4) for various reasoning and conversation tasks - Code-specific models (qwen2.5-coder) for programming assistance - Vision-capable models (granite3.2-vision, llama3.2-vision) for image analysis - Maintains conversation memory for consistent interactions - Processes everything locally for complete privacy and data security Setup 1. Ensure you have Ollama installed and running locally 2. Pull the required models mentioned in the workflow using Ollama CLI (e.g., ollama pull phi4) 3. Configure the Ollama API credentials in n8n (default: 4. Activate the workflow and start interacting through the chat interface How to customize this workflow to your needs - Add or remove models from the router's decision framework based on your specific Ollama collection - Adjust the system prompts in the LLM Router to prioritize different model selection criteria - Modify the decision tree logic to better suit your specific use cases - Add additional preprocessing steps for specialized inputs This workflow demonstrates how n8n can be used to create sophisticated AI orchestration systems that respect user privacy by keeping everything local while still providing intelligent model selection capabilities.
How to import this n8n workflow
- 1
Download the workflow JSON file after purchase.
- 2
Open n8n → click the menu → Import from File.
- 3
Select the downloaded JSON and import.
- 4
Set up credentials for each node that requires them.
- 5
Click Execute Workflow to test, then activate.
Setup guide
Setup guide included
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- JSON blueprint — instant download
- Setup guide PDF included
- 5 downloads · valid 30 days
- Works with n8n
Need help setting this up?
Book a 3-hour live setup session with an Agility consultant.
- Configure live on Google Meet / Zoom
- Free follow-up if workflow has defects
- Platform expert assigned to you