Token calculator

How the token calculator works

Using our token calculator, you can:

• Find out the number of tokens, characters, and words in one or more sentences or paragraphs.
• Upload a document to analyze the number of tokens in it.
• A visual breakdown of the number of tokens in any given text.
• Select from several models such as GPT, Claude, Gemini, etc, to calculate tokens for.

As our calculator supports multiple models, you can get a full picture of how different Large Language Models (LLMs) handle tokens. This also means that the number of tokens in a single phrase or sentence varies from one model to another.

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While we use tokens for LLMs, most people are not informed about what it is and the process behind them. When an LLM learns or generates information, it undergoes a process called tokenization.

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Understanding tokenization and tokens

To understand how LLMs work, it is important to learn about tokenization and tokens. Here is a brief of how that works.

What is tokenization?

LLMs do not simply process text in a conventional manner as they convert any information given into smaller units called tokens. This process of turning text to conversation is called tokenization.

To enable this process, each LLM makes use of a tokenizer like OpenAI uses tiktoken for their GPT models. Using tokenization, LLMs can convert text into tokens to understand information and generate appropriate responses in any language.

What are tokens and how are they counted?

Tokens are smaller units of text that are created through tokenization for LLMs to process. However, there is no fixed definition of what tokens are as each tokenizer handles the breakdown of text differently.

There are some general rules of defining tokens in English and here they are:

• 1 token ~ 4 characters or ¾ of a word
• 100 tokens ~ 75 words
• 1-2 sentence ~ 30 tokens
• 1 paragraph ~ 100 tokens
• 1 document ~ 3000 tokens (about 2250 words)
• Certain special characters (such as ! or .) = 1 token

With these guidelines, you can estimate how tokens work but it is always better to use a calculator like the one above to calculate the number of tokens for popular LLMs.

Tokenizers used by prominent Large Language Models

As mentioned earlier, each tokenizer generates a different number of tokens from a text. For example, OpenAI’s tiktoken defines tokens differently than SentencePiece does for LLaMa/Gemini.

It is also important to note that each model has its respective token limit. That said, here are the popular LLMs and the respective tokenizers they use to break down sentences or paragraphs into tokens.

As the number of tokens differs from one model to other, that also affects the cost to use each LLM for input or output text.

How much do tokens cost?

As mentioned a little earlier, each model calculates tokens differently, and the cost of tokens can largely vary due to that. Thus, to learn about the different costs of using tokens on different LLMs, you can go to the pricing pages of the respective models as show below. :

As for Meta’s LLaMA, it is completely open-source, thus the pricing of the model depends based on different providers. This applies to DeepSeek V3 as well if any such provider is using the open-source version and not the API as listed above.

To learn more about the pricing for these two open-source models in customer service, check out our pricing page and learn how we utilize it to help businesses serve customers better.

Why Are Tokens Important For You and Your Business?

As the world moves toward AI automation and generation, learning about tokens becomes extremely important to utilize LLMs efficiently. Businesses will utilize LLMs through chatbots, where a knowledge base can be trained and utilized for enhanced responses.

This applies to REVE Chat as we utilize Brain AI to train knowledge bases, augment chatbots, and provide customers with personalized replies and unique experiences. This makes learning about LLMs very important to optimize chatbots in terms of operational costs, efficient workflows, and more. Here are the main reasons why tokens are important for businesses.

• Accurate cost estimation: Token usage directly impacts chatbot operational costs, and knowing about the process helps you avoid unexpected expenses.
• Smart model selection: Choose models with the right token limits and costs that fit your chatbot’s needs and company budgets.
• Optimized chatbot responses: Create optimized responses to reduce token usage, reducing cost and avoiding hitting token limits.
• Scalable chatbot operations: Use token-efficient techniques to handle high volumes without skyrocketing costs.

Thus, learning more about LLMs helps you with implementing the right one for your business and achieving reduced costs and higher efficiency.