OpenAI Api pricing uses both the length of text you enter as a prompt and the length of text generated by the GPT model to calculate the price.
OpenAI ChatGPT Token Calculator uses 750 words = 1000 Tokens. The Rates are in USD (US Dollars). You can tokenize your full text with our tokenizer calculator and check the tentative cost as per OpenAI standards.
Table of Contents
The table below shows the Value of Input Rate and Output (per 1k token) as per OpenAI Pricing latest update
|GPT-3.5 Turbo Model
|$0.0015 / 1K tokens
|$0.002 / 1K tokens
|$0.003 / 1K tokens
|$0.004 / 1K tokens
|GPT 4 Model
|$0.03 / 1K tokens
|$0.06 / 1K tokens
|$0.06 / 1K tokens
|$0.12 / 1K tokens
|GPT 4 Turbo Model
|GPT-4-1106-preview 128K context
|$0.01 / 1K tokens
|$0.03 / 1K tokens
|GPT-4-1106-Vision-preview 128K context
|$0.01 / 1K tokens
|$0.03 / 1K tokens
A useful guideline is that approximately one token corresponds to about four characters of text in common English. This means that roughly three-fourths of a word are represented by one token. So, if you have 100 tokens, it would be approximately equal to 75 words.
Understanding ChatGPT Pricing:
OpenAI offers two variants of ChatGPT – GPT-4 and GPT-3.5 Turbo – each with different capabilities and pricing based on the context window used during interactions. The context window determines the number of tokens the model processes for input and output to calculate the chatgpt API pricing.
- 8K Context: $0.03 per 1,000 tokens for input, and $0.06 per 1,000 tokens for output.
- 32K Context: $0.06 per 1,000 tokens for input, and $0.12 per 1,000 tokens for output.
- GPT-3.5 Turbo:
- 4K Context: $0.0015 per 1,000 tokens for input, and $0.002 per 1,000 tokens for output.
- 16K Context: $0.003 per 1,000 tokens for input, and $0.004 per 1,000 tokens for output.
- GPT-4 Turbo:
- 128K Context: $0.01 per 1,000 tokens for input, and $0.03 per 1,000 tokens for output.
- 128K Vision Context: $0.01 per 1,000 tokens for input, and $0.03 per 1,000 tokens for output.
What is Context in GPT?
Wondering what is 8k and 32k context in the models above? It basically means how much data the model can process during a conversation. if you converse beyond the limit the model may forget the previous context and may not be able to relate to it.
So basically greater the context of the Model the better it will be to process our prompts and generate outputs.
What’s the difference between the 8k and 32k models of GPT 4?
As said above the numbers “8k” and “32k” refer to the sizes of the models in terms of parameters or tokens. A larger number of parameters or tokens indicates a more powerful and capable model in terms of generating human-like text and understanding context.
ChatGPT Pricing Calculator:
The Above ChatGPT Pricing Calculator is a powerful and user-friendly tool that allows you to estimate the total cost of using ChatGPT based on your specific input and output requirements.
How to Use the ChatGPT Pricing Calculator:
Using the ChatGPT Pricing Calculator is easy and straightforward. Here’s a step-by-step guide to help you make the most of this tool:
1. Enter the Expected Word Count of the Generated Output: Enter the number of words you asked chatgpt to return as output . Here it is 800 words.
2. Input Prompts Word count: Enter the number of words you plan to enter as a prompt. Like “Write a blog post of 800 words on Topic “How to lose weight”. Use headings and FAQs” has 18 words.
3. Select the per-day usage : Enter how many times the gpt model will be used in a day. ( e.g An employee using 5 times a day to generate blog output)
4. Enter the Monthly Usage: Enter how many times the call will be done monthly. (e.g the employee uses it 20 days per month)
5. The number of tokens will be auto calculated. Based on the number of text used to instruct the model and the amount of text generated as output.
5. Your Usage Estimated Cost for GPT 3.5 Turbo and GPT 4 will be calculated and will be populated in the respective fields allowing you to plan your budget accordingly.
Optimizing Conversations and Costs:
The ChatGPT Pricing Calculator empowers users in several ways:
- Context Window Selection: You can choose the most suitable context window based on your needs, ensuring a seamless conversation experience.
- Budget-Friendly Interactions: By estimating costs beforehand, users can plan interactions that align with their budget constraints.
- Token-Efficient Conversations: Understanding token usage enables users to keep conversations concise and efficient, minimizing unnecessary expenses.
Tips for Optimized API usage cost
You do not need to use the latest GPT version for your API usage , as some of the prior models are good enough to generate content for variety of use cases . It’s best to use the combination of OpenAI GPT models GPT-3.5 Turbo, GPT-4, or GPT-4 Turbo for different calls within your process. This helps in optimizing the overall cost.
Here are some tips for minimizing costs while using these models:
- Start with GPT-3.5 Turbo: It’s often cost-effective.
- Adjust Parameters: Experiment with temperature and max tokens for optimal results.
- Craft Clear Prompts: Improve efficiency with well-crafted prompts.
- Batch Requests: Send multiple requests in one call to save costs.
- Monitor Response Length: Shorter responses cost less.
- Token Management: Minimize token usage for cost savings.
- Cache Responses: Avoid unnecessary API calls by caching static content.
- Manage Rate Limits: Stay within rate limits to prevent extra costs.
- Consider GPT-4 Models: If needed, explore GPT-4 or GPT-4 Turbo for advanced capabilities.
- Iterative Optimization: Regularly review and optimize based on usage and feedback.
What are tokens in the context of ChatGPT?
Tokens are the fundamental units of text that ChatGPT processes. They can range from individual characters to entire words, and the total number of tokens affects the cost and length of conversations.
How are tokens related to words in ChatGPT?
In general, 1,000 tokens in ChatGPT roughly equate to about 750 words. Understanding token counts helps users estimate the cost and optimize the length of interactions.
How is ChatGPT priced based on tokens?
ChatGPT is priced per 1,000 tokens, and the cost depends on the variant (e.g., GPT-4 or GPT-3.5 Turbo) and the context window used for input and output.
What is the difference between GPT-4 and GPT-3.5 Turbo in terms of pricing and tokens?
GPT-4 and GPT-3.5 Turbo have different pricing structures and token costs based on the context window used during interactions. GPT-4 offers variants with 8K and 32K context, while GPT-3.5 Turbo provides 4K and 16K context options.
Can I optimize token usage to manage costs better?
Yes, optimizing token usage is essential to manage costs effectively. Users can aim for concise prompts and truncate or limit the length of generated output to stay within their budget.
Can I switch between GPT-4 and GPT-3.5 Turbo based on my requirements?
Yes, users can choose the most suitable variant based on their desired context window and pricing options.
What happens if my conversation exceeds the token limit in my pricing plan?
If a conversation exceeds the token limit in your chosen plan, additional charges may apply. It’s essential to keep track of token usage to avoid unexpected costs.
How can I estimate the token count for my input and output?
Use the ChatGPT Token Calculator at the top of the Post, which can estimate the cost of token counts based on the number of words in your input prompt and the length of the generated output.