Prompt Token Counter
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tokencounter.org
Prompt Token Counter
Prompt Token Counter is a web-based tool designed to help users calculate the number of tokens in their prompts before submitting them to OpenAI's language models, including GPT-4o, GPT-4, and GPT-3.5 Turbo. This is crucial for managing costs and staying within the model's token limits.
The tool allows to accurately count tokens, ensuring that prompts and responses fit within the specified limitations of the model. By doing this, the prompt token counter helps you stay within model limitations, control costs, manage responses and create an efficient communication.
tokencounter.org
Token Counter is a tool designed to help users determine the token count of text inputs for various OpenAI models, such as GPT-4 and GPT-3.5. It accurately converts user-provided text into tokens and estimates corresponding costs.
The tool offers an efficient solution for those who frequently utilize AI models, providing accurate token counts and calculating the financial implications of using these models. Token Counter utilizes algorithmic computation to convert text to tokens because it's not direct one-to-one conversion.
Prompt Token Counter
Pricing
tokencounter.org
Pricing
Prompt Token Counter
Features
- GPT-4o Support: Count tokens for the GPT-4o model.
- GPT-4 Support: Count tokens for the GPT-4 model.
- GPT-3.5 Turbo Support: Count tokens for ChatGPT (GPT-3.5 Turbo).
- Davinci Support: Count tokens for the Davinci Model.
- Curie Support: Count tokens for the Curie Model.
- Babbage Support: Count tokens for the Babbage Model.
- Ada Support: Count tokens for the Ada Model.
tokencounter.org
Features
- Token Calculation: Converts user text input into the corresponding token count for different OpenAI models.
- Cost Estimation: Calculates the cost associated with the token count based on the selected AI model.
- Multiple Model Support: Provides token counts for various models, including GPT-4, GPT-3.5, Davinci, and Babbage.
- Accurate Conversion: Uses algorithmic computation to convert text into tokens, ensuring precise results.
Prompt Token Counter
Use cases
- Preparing prompts for OpenAI API calls.
- Managing costs associated with token usage.
- Ensuring prompts stay within model-specific token limits.
- Optimizing prompts for efficient communication with language models.
tokencounter.org
Use cases
- Estimating costs for using AI models.
- Calculating token counts for different OpenAI models.
- Converting text into tokens for budget planning.
- Managing expenses related to AI model usage.
Prompt Token Counter
FAQs
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What is a token?
In natural language processing, a token is the smallest unit of text, such as a word, character, or subword, used for processing by machine learning models.What is a prompt?
A prompt is the initial input given to a language model to initiate a task or generate a response, such as a question or a statement.
tokencounter.org
FAQs
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Why do different models have different token counts?
Different models have varying token counts due to differences in tokenization strategies. Each model, like GPT-3, GPT-3.5, and GPT-4, uses a unique tokenizer, impacting how text is broken down into tokens.How much does token count?
The cost of token usage varies by model. For example, GPT-4 (turbo) costs $10.00 per 1 million input tokens and $30.00 per 1 million output tokens, while GPT-3.5 (turbo-0125) costs $0.50 per 1 million input tokens and $1.50 per 1 million output tokens.
Prompt Token Counter
Uptime Monitor
Average Uptime
99.86%
Average Response Time
153.3 ms
Last 30 Days
tokencounter.org
Uptime Monitor
Average Uptime
99.9%
Average Response Time
302.4 ms
Last 30 Days
Prompt Token Counter
tokencounter.org
