Understanding AI credits

The combination of AI and automation has become a game-changer. You can now leverage the power of GPT and PhantomBuster to enrich data, gain insights, and create personalized outreach messages on a larger scale. In this article, we will explain what you need to know about AI credits, and you’ll gain valuable insights for managing costs in your AI projects!


At PhantomBuster, we understand the importance of flexibility and convenience when it comes to managing AI credits. That's why we offer two options:

1) PhantomBuster AI Credits

- included in all our current paid subscription plans.

- output the cost in credits

2) OpenAI

- your personal ChatGPT account tokens (currently available only with our AI Advanced Enricher).

- output the cost in tokens

Both options work in a similar manner, but the key difference lies in where the credits or tokens are spent. This allows you to choose the option that best suits your requirements and ensures efficient utilization of your credits or tokens, whether you prefer the integrated PhantomBuster AI version or the direct connection to your Chat GPT account.

Our paid subscriptions come with AI credits included - if you're using your personal ChatGPT account and run out of tokens, we encourage you to spend the credits that are included in your PhantomBuster plan.

GPT Breakdown Table.png

Setting up your Phantom

When setting up your Phantom, you will have to choose the “GPT Model” from a list of options:

GPT Options.png

For PhantomBuster<>OpenAI integration, we output the cost in credits. The approximate conversion is around 100 tokens equal to 1 credit for GPT-3.5. Find out more information about each plan on our Billing page!

For OpenAI, the cost is measured in tokens rather than credits. In English, a token is roughly equivalent to 4 characters (so 100 tokens is approximately 75 words). The cost in dollars depends on the model used, as GPT-4.0 will be more expensive than GPT-3.5 for the same number of tokens. The exact pricing details can be found on OpenAI's website, as they provide the token-based cost structure for their models.

The Phantom's output will show the number of credits or tokens that PhantomBuster will use to solve their prompt.

Note: When converting text into tokens, it's essential to remember that we cannot determine the exact number of tokens a customer's request may consume as it varies depending on the precise phrase employed. For example, different words can take up different numbers of tokens, leading to variations in the token count for different phrases. A simple phrase like "I love cats" requires only three tokens, whereas its French translation "J'aime les chats" demands six tokens. You can find out more information on the Tokenizer page!

If you think this article does not address your issue, please contact Support directly. We are continuously improving, so your feedback means the world to us!

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