If you follow the development of artificial intelligence (AI) tools with interest or use them yourself, you've likely come across the term "AI token." No, we're not talking about tokens used in cryptocurrencies or terms like AI coins or crypto coins.
In this context, tokens are units that enable the calculation of costs for using language models like ChatGPT. But that's not all. They also help determine the length of the input and output, which are equally important for the final calculation of an AI model's usage costs.
Does that sound complicated? Don't worry—it isn't. If you need help understanding what AI tokens are all about, this article explains what they are and how they influence the costs of using generative AI.
Understanding AI Tokens
Tokens are units of text in artificial intelligence technology and tools like ChatGPT (AI models). They can be as long as a word or consist of just a few characters, including spaces. How tokens are counted also depends on the user's language.
As is well known, ChatGPT works best with the English language, so the way it counts tokens differs significantly when we communicate in other languages. For example, if we examine how a specific text fragment is broken into tokens using tools like OpenAI's Tokenizer, we can observe the following:
Request in German: Wie schreibt man ein Gedicht?
Request in English: How to write a poem?
The German request is split as follows:
- Wie
- \_sch (with a space)
- re
- ibt
- \_man
- \_ein
- \_Ged
- icht
- ?
This results in a total of nine tokens and 29 characters.
In contrast, the same request in English consists of the following tokens:
- how
- \_to
- \_write
- \_a
- \_poem
- ?
This sentence consists of six tokens and 20 characters.
As you can see, in this case, we saved three tokens with the same command but in English. That might not seem like much, but ChatGPT is typically used to process large amounts of text, so such seemingly small differences can quickly lead to high costs.
According to calculations provided by OpenAI, one token in English corresponds to four characters, and therefore, 100 tokens roughly equal 75 words.
The Importance of AI Tokens and Their Impact on Costs
Tokens play a crucial role in using AI tools. Ultimately, the costs you incur when using them are calculated based on tokens. They function as a kind of AI currency. That's why it's worth examining a few elements that influence the number of tokens.
Language
As mentioned earlier, language can significantly impact the number of tokens and the cost of using a chatbot. Interestingly, the tokenizer counts German characters with diacritical marks like ä, ü, and ö as one token. However, for languages like Polish with characters such as ł, ś, and ć—especially when written in uppercase—they are treated as special characters and counted as two tokens.
Input and Output Length
Keep in mind that the final costs aren't solely based on the number of tokens in the input data. The total costs consist of your input: the prompt and context (which can include additional text fragments uploaded to a chatbot or instructions the bot must follow) and the output—the response generated by the system.
Sometimes the situation looks like this: The input is very detailed and correspondingly long, while the system's response is short. You need to manipulate the input to make the generated response worthwhile.
Understanding the dependencies between these three parameters allows you to manage and optimize costs efficiently.
Token Limits
Moreover, text generators like ChatGPT have a built-in token limit (e.g., 4069). If you exceed this limit, you must shorten your inputs or delete fragments of a conversation. However, the second solution can cause the bot to lose essential context elements, resulting in lower-quality responses.
Cost Management — Useful Tips
Managing the costs associated with interacting with generative AI systems requires balancing the length of your input and output. So, what can you do to get the most for the lowest price?
AI Token Tips and Tricks
Be Concise and Precise
Short prompts not only reduce the number of tokens but also lead to more satisfactory responses. Therefore, think carefully about how you structure your prompts and decide how much context is sufficient to achieve the best results. Also, the fewer tokens you use in your input, the more remain for generating the output.
Also, remember that there are some unique characters that ChatGPT doesn't include in the costs, such as "<|endoftext|>," which signals the end of the text or a specific fragment. However, there are others like "\n" that are subject to standard counting. What does all this mean? It's worth experimenting with tokens and searching online for helpful advice.
Pay Attention to the Language You Use
The grammar of different languages can vary fundamentally. Whether you choose to create prompts in English, German, or Polish significantly impacts how the system counts tokens. Therefore, you must be aware of these differences and choose the option that offers cost advantages and suits your use case.
Remember Token Limits
It's very easy to get caught up in a long conversation with a bot unnoticed, and before you know it, you've used all your tokens. There are a few ways to avoid this problem. The first is to delete previous messages, but you must be aware that you'll lose context. A better solution is to summarize the key points of the conversation and then delete the older messages. You can also choose a different approach and instruct the bot using system messages on how to respond. This way, you can save tokens and time correcting chatbot outputs.
Choose the Appropriate Language Model
The cost of tokens depends on the language model you use. OpenAI has already released several versions of ChatGPT: ChatGPT Legacy, ChatGPT-3.5 Turbo, ChatGPT-4, and ChatGPT-4 Turbo. The choice of the appropriate model depends on the goals you're trying to achieve. If you don't need very high-quality bot responses for some reason, older versions of the language model may suffice. These models differ in the quality of generated content and the price you pay per token.
It's also worth knowing about tools that help predict the costs of chatbot usage. For ChatGPT, these include the aforementioned Tokenizer and a handy Python library called Tiktoken. Thanks to these tools, you can estimate the costs of your inputs and decide whether a particular conversation should be split into multiple segments.
Frequently Asked Questions
How Do AI Tokens Work?
AI tokens are units of text that AI models like ChatGPT use to process input and output. They help calculate usage costs based on the number of tokens consumed during interactions. Each token can represent a word, part of a word, or even a space, depending on the language and context.
Why Does Language Affect Token Count?
Different languages have varying grammatical structures, which influence how text is broken into tokens. For example, English often requires fewer tokens than German or Polish for the same phrase due to differences in word formation and character usage.
Can I Reduce My AI Token Usage?
Yes, by crafting concise prompts, using efficient language, and monitoring conversation length. Tools like token counters can help you estimate costs before submitting requests, enabling better cost management.
What Happens If I Exceed the Token Limit?
If you exceed the token limit of an AI model, you may need to shorten your input or delete parts of the conversation. However, this can lead to loss of context, potentially reducing the quality of the AI's responses.
Are There Tools to Help Manage Token Usage?
Yes, tools like OpenAI's Tokenizer and the Tiktoken Python library allow users to count tokens in their text, estimate costs, and optimize inputs for better efficiency.
How Do I Choose the Right AI Model for My Needs?
Consider factors like response quality, cost per token, and specific use cases. Older models may be more cost-effective for simple tasks, while advanced models like GPT-4 offer higher quality at a higher price.
Summary
In the context of generative artificial intelligence, AI tokens are text units that determine the costs users pay when using ChatGPT. The number of tokens depends on the grammatical structure of the language and varies accordingly.
Understanding how AI tokens work is essential for efficiently using language models. The ability to count them is crucial for optimizing costs and making the best possible use of tools like ChatGPT. Skillful management of AI tokens allows you to control expenses and ensure you can seamlessly adhere to predefined limits.
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