Token Counter

Simple tool to count number of tokens in a text. Based on tiktoken by OpenAI. Select the model and enter the text to get the token count.

Why Count Tokens?

In AI models, especially language models like GPT-4, GPT-3.5 where users are charged per token, a tokenizer or token counter can be quite beneficial. Here are a few reasons why a token counter is useful:

1. Budget Management: Given the fact that every token carries a cost, token counters allow users to monitor their consumption and manage their budget. They can keep track of how many tokens are being used per request.

2. Improved Efficiency: It allows users to tailor their inputs to use minimal tokens while still getting desired outputs. This could mean rephrasing sentences, removing superfluous language, or preferencing shorter words when possible.

3. Avoiding Excess Costs: If a model has the maximum tokens allowed per request, a token counter can help ensure that requests do not exceed this limit and users are not charged for tokens they did not intend to use.

4. Understanding Output Length: In models like GPT-4, the output tokens also matters. Having a tokenizer can help understand how long the model's response will be, which eventually helps with better planning.

5. Performance Optimization: Making good use of tokens could optimize the processing speed and system performance. Large token loads can slow down the processing speed, thereby affecting the overall performance.

In summary, a tokenizer or a token counter can be an essential tool when it comes to using token-based AI models to balance costs, performance and the overall functioning.