🔥 Key Takeaways:
🔥 Using free LLMs for basic tasks can significantly reduce costs, with some models matching the performance of paid options.
🔥 Implementing a hybrid model with paid LLMs for complex tasks and free models for simple tasks can lead to substantial cost savings.
🔥 Gradually updating workflows with free models and monitoring performance and costs can help achieve the best results.

My Openrouter usage bill

https://www.youtube.com/watch?v=HEJc6V1vPRI

Last month, I got a shocking $100 bill for my AI automation credits. I was shocked how fast A.I. api costs can add up. But here’s the good news - I found a way to cut those costs by 80% while keeping my automations running smoothly.

If you’re using n8n or Make.com for AI-powered workflows, you know how quickly those API calls add up. I’ve spent the last three months testing every LLM option out there, from GPT-4 to Claude to Gemini. I’ll show you exactly how I slashed my costs using Openrouter while maintaining high-quality outputs.

The Cost Problem Is Real

I use AI for content creation, linkedin posts, and even labelling my home items. Each workflow seemed cheap at first - just pennies per API call. But with thousands of automated tasks running daily, those pennies turned into hundreds of dollars.

Here’s what I was paying monthly:

  • Content and code generation: $40 (GPT-4)

  • Writing content: $50 (Claude)

  • Social media: $10 (Various LLMs)

The worst part? I was often using expensive models for simple tasks that cheaper or free alternatives could handle just fine.

Free LLMs Changed the Game

I started testing free alternatives like Google’s Gemini and Meta’s Llama. The results surprised me:

  • Gemini matched GPT-3.5 on basic writing tasks (i.e. keywords, titles)

  • Llama excelled at text classification

  • Both handled sentiment analysis perfectly

For simple tasks like email summarization or basic content creation, these free models worked great. But I still needed premium LLMs for complex work.

  • Basic content = Gemini

  • Data analysis = Llama 2

  • Complex writing = Claude

This strategy alone cut my costs by 60%. But the real magic happened when I started tracking usage patterns.

Making It Work in Your Workflows

n8n doesn’t have a openrouter node, so you’ll need to use the http request node.

{
"model": "meta-llama/llama-3.1-70b-instruct:free",
"messages": [
{
"role": "user",
"content": "[your prompt instructions here]"
}
]
}

For make.com, you can buy the openrouter module.

The Results Speak for Themselves

After one month:

  • Old monthly cost: $100

  • New monthly cost: $10

  • Quality difference: Negligible

  • Time saved: 2 hours per week

The best part? Seeing $0 charge for my usage.

Take Action Today

  1. Sign up for Openrouter

  2. Test free models for your basic tasks

  3. Update your workflows gradually

  4. Monitor performance and costs

Start small. Try one workflow with a free model. Track the results. You might be surprised at how much you can save without sacrificing quality.

Want to learn more? I’ve created a detailed setup guide. Drop a comment below, and I’ll share it with you.