Compare LLM token costs across 350+ models with OpenRouter

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Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

This n8n template lets you run prompts against 350+ LLM models and see exactly what each request costs with real time pricing from OpenRouter Use cases are many: Compare costs across different mode...

Best for

Engineering automation workflows
AI Chatbot automation workflows
advanced n8n builders looking for reusable templates

Tools used

@n8n/n8n-nodes-langchain.chattrigger, n8n-nodes-base.executeworkflowtrigger, n8n-nodes-base.code, @n8n/n8n-nodes-langchain.code, n8n-nodes-base.filter, n8n-nodes-base.form, n8n-nodes-base.splitout, n8n-nodes-base.stickynote

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Philflow.

Original n8n.io source

1.1 Workflow description

Title: Compare LLM token costs across 350+ models with OpenRouter
Workflow name: Compare LLM token costs across 350+ models with OpenRouter

This n8n template lets you run prompts against 350+ LLM models and see exactly what each request costs with real-time pricing from OpenRouter

Use cases are many: Compare costs across different models, plan your AI budget, optimize prompts for cost efficiency, or track expenses for client billing!

Good to know

OpenRouter charges a platform fee on top of model costs. See OpenRouter Pricing for details.
You need an OpenRouter account with API credits. Free signup available with some free models included.
Pricing data is fetched live from OpenRouter's API, so costs are always up-to-date.

How it works

All available models are fetched from OpenRouter's API when you start.
You select a model and enter your prompt via the form (or just use the chat).
The prompt is sent to OpenRouter and the response is captured.
Token usage (input/output) is extracted from the response using a LangChain Code node.
Real-time pricing for your selected model is fetched from OpenRouter.
The exact cost is calculated and displayed alongside your AI response.

How to use

Chat interface: Quick testing - just type a prompt and get the response with costs.
Form interface: Select from all available models via dropdown, enter your prompt, and get a detailed cost breakdown.
Click "Show Details" on the result form to see the full breakdown (input tokens, output tokens, cost per type).

Requirements

OpenRouter account with API key (Get one here)

Customising this workflow

Add a database node to log all requests and costs over time
Connect to Google Sheets for cost tracking and reporting
Extend with LLM-as-Judge evaluation to also check response quality

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - When chat message received

Type / Role: @n8n/n8n-nodes-langchain.chatTrigger - chatTrigger
Config choices: Version 1.4

Block 2 - When Executed by Another Workflow

Type / Role: n8n-nodes-base.executeWorkflowTrigger - executeWorkflowTrigger
Config choices: Version 1.1

Block 3 - Code in JavaScript

Type / Role: n8n-nodes-base.code - code
Config choices: Version 2

Block 4 - LangChain Code

Type / Role: @n8n/n8n-nodes-langchain.code - code
Config choices: Version 1

Block 5 - Filter

Type / Role: n8n-nodes-base.filter - filter
Config choices: Version 2.2

Block 6 - Code in JavaScript1

Type / Role: n8n-nodes-base.code - code
Config choices: Version 2

Block 7 - Form

Type / Role: n8n-nodes-base.form - form
Config choices: Version 2.3

Block 8 - Form1

Type / Role: n8n-nodes-base.form - form
Config choices: Version 2.3

Block 9 - Split Out

Type / Role: n8n-nodes-base.splitOut - splitOut
Config choices: Version 1

Block 10 - Split Out1

Type / Role: n8n-nodes-base.splitOut - splitOut
Config choices: Version 1

Block 11 - Sticky Note1

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 12 - Respond to Chat

Type / Role: @n8n/n8n-nodes-langchain.chat - chat
Config choices: Version 1

Block 13 - Sticky Note2

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 14 - On form submission

Type / Role: n8n-nodes-base.formTrigger - formTrigger
Config choices: Version 2.3

Block 15 - Sticky Note

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 16 - OpenRouter

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenRouter - lmChatOpenRouter
Config choices: Version 1

Block 17 - Backend

Type / Role: n8n-nodes-base.executeWorkflow - executeWorkflow
Config choices: Version 1.3

Block 18 - Backend1

Type / Role: n8n-nodes-base.executeWorkflow - executeWorkflow
Config choices: Version 1.3

Block 19 - Get Openrouter models

Type / Role: n8n-nodes-base.httpRequest - httpRequest
Config choices: Version 4.3

Block 20 - Get Openrouter models1

Type / Role: n8n-nodes-base.httpRequest - httpRequest
Config choices: Version 4.3

Block 21 - Sticky Note3

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

3. Summary Table

Workflow	Compare LLM token costs across 350+ models with OpenRouter
Complexity	advanced
Nodes	21
Categories	Engineering, AI Chatbot
Author	Philflow
Published	24 Dec 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/12100/12100.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
4. Test with sample data

Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
5. Activate and monitor

Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Download workflow JSON Original n8n.io source Engineering workflows AI Chatbot workflows

Frequently asked questions

What does Compare LLM token costs across 350+ models with OpenRouter do?

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Engineering, AI Chatbot use case.

Philflow

1 workflow

Nodes

@n8n/n8n-nodes-langchain.chattrigger n8n-nodes-base.executeworkflowtrigger n8n-nodes-base.code @n8n/n8n-nodes-langchain.code n8n-nodes-base.filter n8n-nodes-base.form n8n-nodes-base.splitout n8n-nodes-base.stickynote

Complexity

advanced

Published 24 Dec 2025

Likes 0

View on n8n.io Download Workflow

Install path: /data/workflows/12100/12100.json

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Compare LLM token costs across 350+ models with OpenRouter

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

This n8n template lets you run prompts against 350+ LLM models and see exactly what each request costs with real-time pricing from OpenRouter

Good to know

How it works

How to use

Requirements

Customising this workflow

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - When chat message received

Block 2 - When Executed by Another Workflow

Block 3 - Code in JavaScript

Block 4 - LangChain Code

Block 5 - Filter

Block 6 - Code in JavaScript1

Block 7 - Form

Block 8 - Form1

Block 9 - Split Out

Block 10 - Split Out1

Block 11 - Sticky Note1

Block 12 - Respond to Chat

Block 13 - Sticky Note2

Block 14 - On form submission

Block 15 - Sticky Note

Block 16 - OpenRouter

Block 17 - Backend

Block 18 - Backend1

Block 19 - Get Openrouter models

Block 20 - Get Openrouter models1

Block 21 - Sticky Note3

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions