Track LLM costs and usage across OpenAI, Anthropic, Google and more

Description

Installation Steps

Go to Settings → n8n API and create an API key
Add it as credential for the Get Execution Data node
Review model mappings in Standardize Names node
Review pricing in Model Prices node

To Monitor a Workflow

Add Execute Workflow node at the end of your target workflow
Select this monitoring workflow
Turn OFF "Wait For Sub-Workflow Completion"
Pass { "executionId": "{{ $execution.id }}" } as input

Prerequisites

Enable "Return Intermediate Steps" in your AI Agent settings for best results.

Supported Providers

OpenAI · Anthropic · Google · DeepSeek · Meta · Mistral · xAI · Cohere · Alibaba Qwen · Moonshot Kimi

120+ Model Variations Mapped
Includes all versioned variants (e.g., gpt-4o-2024-08-06 → gpt-4o)

Prices sourced from official provider pages (March 2026)

Output Data

Per LLM Call
Cost Breakdown (prompt, completion, total USD)
Token Metrics (prompt, completion, total)
Performance (execution time, finish reason)
Content Preview (first 100 chars I/O)
Model Parameters (temp, max tokens, timeout)
Execution Context (workflow, node, status)
Flow Tracking (previous nodes chain)

Summary Statistics
Total executions and costs
Breakdown by model type
Breakdown by node
Average cost per call
Total execution time

💡 You can do anything with this data!

Store in a database for historical tracking
Send to Teams as a cost alert
Build dashboards with the summary data
Set budget thresholds and trigger warnings
Export to Google Sheets for reporting