AI Costs: Tokens, Credits, and What They Mean for you and your team
AI is everywhere these days, but how much does it actually cost to use? If you’ve played with ChatGPT, Claude, or similar tools, you’ve probably seen terms like tokens and credits. Here’s a quick guide to what they mean—and how to avoid surprises on your bill.
What Are Tokens?
AI models don’t count words—they count tokens. A token might be a word, part of a word, or even just a character. For example, “Hello world!” is three tokens: “Hello”, “world”, and “!”. Both your input and the AI’s output use tokens, so longer conversations or big documents use more.
What Are Credits?
Credits are how you pay for AI use. Some platforms give you monthly credits, others charge by the number of tokens you use (like $0.002 per 1,000 tokens for GPT-4.1 input). More complex tasks—like generating images or analyzing audio—cost more credits because they use more computing power.
Model Costs: Not All AI Is Priced the Same
Different models have different strengths—and prices. Here’s a quick snapshot:
| Model | Use Case | Input (per 1K tokens) | Output (per 1K tokens) |
|---|---|---|---|
| GPT-4.1 | Advanced reasoning, LLM apps | $0.002 | $0.008 |
| GPT-4.1 Mini | Fast, light text tasks | $0.0004 | $0.0016 |
| Claude 3 Opus | Deep comprehension, long context | $0.015 | $0.075 |
| Claude 3 Sonnet | Budget-friendly summaries | $0.003 | $0.015 |
Pro tip: Use lighter models for routine jobs (like parsing invoices), and save the heavyweights for complex or creative work.
Watch Out for Hidden Costs
It’s easy to burn through credits without realizing it—especially if you’re debugging code, running automations, or just chatting a lot. Always keep an eye on your usage dashboard, set limits, and look for ways to optimize.
You are out of Credits
I’ve often found myself running out of tokens on various tools. It all began with ChatGPT when I was using the free version—I was conducting research and quickly used up my tokens. Now, I am a subscriber. This trend continued when I started using CoPilot in my development work and later explored tools like Loveable.dev and Bold.new.
I now have multiple subscriptions, but I have trained myself to effectively utilize the credits and tokens in my development and workflow processes. How many of you have run out of tokens while in the middle of something you needed to complete?
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Quick Tips to Save on AI
- Keep prompts short and clear.
- Pick the right model for your task.
- Cache results when possible.
- Audit your automations for unnecessary calls.
- Test with limits to avoid runaway costs.
The Bottom Line
Tokens are what you use; credits are how you pay. The model and task you choose are your cost multipliers. Understanding these basics will help you get the most.
What is your experience with Tokens and Credits?