Here's a problem you'll hit if you're building anything with AI:

You want to use GPT-5 Codex for some tasks. Then you hear Claude Code is better. Then you see a tweet that claims Gemini 2.5 Pro is faster and cheaper.

So now you need:

Each one has different pricing. Different billing dashboards. Different ways to check usage.

Your "billing spreadsheet nightmare" = logging into three different sites, downloading three CSVs, manually adding up costs to figure out your actual AI spend.

OpenRouter fixes this: One account. One API key. One bill that shows everything.

Different models are good at different things:

You should be testing different models for different tasks. But most developers don't, because switching is annoying.

OpenRouter removes that friction.

Think of OpenRouter like a router in your home network.

Your laptop doesn't connect directly to every website. It sends requests to your router. The router figures out where to send them.

Without OpenRouter: You need three different code setups. Three API keys. Three billing pages.

With OpenRouter: You write your code once. OpenRouter handles the routing. One API key. One bill.

The code you write is almost identical no matter which model you want to use.

Step 1: Create account

Step 2: Add money

The fee buys you convenience. Instead of managing multiple accounts and bills, you pay one company to handle all the routing and billing. If you're learning and experimenting, the time you save is worth way more than 5.5%. If you're running a massive production app that only uses one model, maybe not.

Step 3: Get your API key

Important: Create a file called .env in your project folder:

Never put API keys directly in your code. Always use environment variables. This keeps them secure.

If you were using OpenAI directly, your code looks like this:

This sends a request directly to OpenAI's servers.

With OpenRouter, three things change:

Everything else stays identical.

Want to try Claude Code instead of GPT-5 Codex? Just change the model name:

Everything else in your code stays exactly the same.

You're building a chatbot. You need it to:

The test: Send the same coding question to three models and compare.

When you run this, you'll discover:

Now you can make an informed choice instead of just using whatever you set up first.

OpenRouter has built-in shortcuts that choose providers for you based on what you care about.

Speed optimization (:nitro):

What this does: Sends your request to the fastest available provider for that model.

When to use: User-facing features where response time matters. If someone is waiting for your chatbot to respond, use :nitro. The extra 100-200ms saved makes the experience feel snappier.

Cost optimization (:floor):

What this does: Sends your request to the cheapest available provider for that model.

When to use: Background tasks where speed doesn't matter. Processing 1000 documents overnight? Use :floor. You'll save 30-40% on costs.

No suffix (default):

What this does: OpenRouter balances speed, cost, and reliability automatically.

When to use: Most of the time. Unless you have a specific reason to optimize for speed or cost, default routing works fine.

Here's a smart hack: use expensive models for hard tasks, cheap models for easy tasks.

Why this works:

Planning requires deep reasoning. You want the smartest model.

Implementation is more straightforward. A cheaper model can handle it.

You get quality where it matters, savings where it doesn't.

Some AI models can "see" images and read PDFs. You can send them files and ask questions about the content.

Sending an image:

What's happening here:

Use cases:

Sending a PDF:

Use cases:

Every API call costs money. Check what you're spending:

What are tokens?

Tokens are chunks of text. Roughly:

You pay for both input tokens (your prompt) and output tokens (the model's response).

Example:

That's a 75x difference between the cheapest and most expensive. Use :floor for tasks where you don't need absolute best quality.

When you're making API calls, things can fail:

Common errors you'll see:

When you're making API calls, things can fail:

What OpenRouter logs:

What OpenRouter doesn't log:

If you need extra privacy: use Zero Data Retention (ZDR):

This ensures OpenRouter only routes to providers that promise not to store your data.

"Invalid API key" error

Check your .env file. Make sure you're using your OpenRouter key, not your OpenAI key. They look similar but they're different.

"Model not found" error

You probably forgot the provider prefix.

Wrong: model: 'gpt-5-codex'

Right: model: 'openai/gpt-5-codex'

Check the full list at openrouter.ai/models

Costs are higher than expected

Check which models you're using. The price difference between models is massive.

Pick one project and spend an hour on it:

Model Comparison Tool: Send the same prompt to GPT-5, Claude, and Gemini. Print response time, token count, cost, and the actual response. See which model you prefer for different tasks.

Image Analyzer: Build a script that takes an image as input, sends it to Claude or GPT-4, asks "What's in this image?" and prints the description.

PDF Summarizer: Read a PDF file, send it to Claude, ask for a summary, and save the summary to a text file.

You'll learn more by building than reading.

OpenRouter is practical. Instead of juggling multiple API keys and billing dashboards, you use one. Instead of rewriting code to test different models, you change one line.

The 5.5% fee? Probably worth it while you're learning and experimenting.

Start small. Make one API call. See how it works. Build from there.

Until next time,
Vaibhav 🤝🏻

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