9 min readMar 14, 2023

ChatGPT Pricing: A Complete Guide to ChatGPT Cost Estimation and Price Optimization

Disclaimer

The information presented in this blog post is based on the official ChatGPT documentation available at https://openai.com/pricing, and is intended to provide a comprehensive guide on ChatGPT pricing. While every effort has been made to ensure the accuracy of the information provided, readers should refer to the official documentation for the most up-to-date and complete information. The author of this blog post assumes no liability for any errors or omissions in the information presented. The strategies and techniques presented are for informational purposes only and are not guaranteed to result in cost savings. Readers should conduct their own cost analysis and seek professional advice before developing and deploying NLP applications

Additional Reference :

ChatGPT is available in preview in Azure OpenAI Service.

Microsoft Azure OpenAI Service pricing

Introduction

Natural Language Processing (NLP) is a rapidly growing field that involves the development of algorithms and models that can understand and generate human language.

ChatGPT is a sophisticated NLP platform that utilizes advanced machine learning algorithms to analyze and create human-like text. Its functionality is extensive, including capabilities such as text completion, text classification, and language translation, which are applicable in various industries such as virtual assistants, chatbots, and content generation.

The versatility of ChatGPT is due to its ability to support a diverse range of tasks. It can assist with generating emails, creating knowledge base articles, answering questions, transforming data into specific formats, generating test cases, and providing software source code support in any programming language. Additionally, ChatGPT can be used to prepare user guides, making it a valuable tool for businesses in different sectors.

However, it is important to be mindful of the potential risks & cost associated with its use

On Security Part

it is crucial to exercise caution when sharing sensitive or personal data, especially in countries governed by GDPR regulations. To provide more insights into these concerns, I have written a blog post that delves deeper into the topic. I believe it may be informative for you, so please give it a read and let me know your thoughts.

https://medium.com/@iamshowkath/ensuring-security-and-privacy-in-nlp-models-like-chatgpt-and-google-bert-54f235248759

On Pricing Part

This blog post provides a comprehensive guide on ChatGPT pricing. You will learn about the different factors that go into calculating the cost of using ChatGPT, as well as various cost estimation techniques and price optimization strategies that can help you develop and deploy NLP applications cost-effectively. Whether you’re a seasoned developer or new to the field, this guide will provide you with valuable insights to help you make informed decisions about ChatGPT pricing.

If you’re developing NLP applications, cost estimation and price optimization are critical factors that can impact your success. By understanding the costs associated with using NLP technologies and implementing effective pricing strategies, you can develop and deploy your applications in a cost-effective manner. This blog post is designed to provide you with the information you need to make informed decisions about ChatGPT pricing, whether you’re building chatbots, virtual assistants, or content generation tools.

Allow me to begin by explaining how to understand the pricing model of ChatGPT

Understanding Tokens in Natural Language Processing (NLP) such as ChatGPT , Google BERT

Understanding tokens is important for understanding how these models (Chat GPT ) are priced and how usage is calculated.

In the case of ChatGPT, tokens are used to measure the amount of usage of the API, and the pricing model is based on the number of tokens used.

One of the fundamental concepts in NLP is the idea of “tokens”, which are essentially the building blocks of language used for analysis and processing. In NLP models like ChatGPT and Google BERT, tokens play a crucial role in understanding and generating natural language text.

Tokens play a crucial role in Natural Language Processing (NLP) as they are used to represent a unit of meaning in a text document. A token is essentially a sequence of characters that can be a word, punctuation mark, symbol, or any other meaningful element of language that is relevant for the given task. Tokenization is the process of breaking down a text document into individual tokens for further analysis or processing.

For instance, consider the sentence “I love eating pizza!”. In this case, the tokens would be “I”, “love”, “eating”, “pizza”, and “!”. NLP models like ChatGPT use tokens to understand and generate natural language text.

In English text, one token is roughly equivalent to four characters or 0.75 words. As a point of reference, the collected works of Shakespeare consist of approximately 900,000 words or 1.2M tokens.

To learn more about tokens and estimate their usage, you can experiment with the interactive Tokenizer tool. You can log in to your account and enter text into the Playground, and the counter in the footer will display the number of tokens in your text.

https://platform.openai.com/tokenizer

In the following sections, Let’s explore how ChatGPT’s pricing model works, how the cost is calculated, and how tokens are used to estimate usage.

ChatGPT Usage:

ChatGPT’s pricing is based on the number of tokens used for both input and output, which are individual units of text, such as words or characters, that the model processes. The cost of using ChatGPT depends on the number of tokens processed and the pricing plan selected.

Refer : https://openai.com/pricing

ChatGPT API Cost:

ChatGPT provides an API for developers to integrate its features into their applications. The API cost is also based on the number of tokens processed and the pricing plan selected. ChatGPT offers a free plan, a standard plan, and a premium plan with custom pricing.

To estimate the cost of using ChatGPT’s API, developers can use the bottom-up estimation technique. They can break down their project into smaller tasks, estimate the number of tokens required for each task, and calculate the cost based on the pricing plan selected.

Let’s assume a developer wants to integrate ChatGPT’s API into their application to provide chatbot functionality to their users. They estimate that on average:

A user will interact with the chatbot for about 10 messages per conversation.
Each message consists of 10 tokens.

Based on this estimate, the developer can calculate the number of tokens their application will use per user per conversation:

The number of tokens per conversation would be 100 tokens (10 messages * 10 tokens per message).

Assuming the developer expects to have 10,000 users per month, and each user engages in 10 conversations per month:

The total number of tokens used per month would be 10,000,000 tokens (100 tokens per conversation * 10 conversations per user per month * 10,000 users).

Using ChatGPT’s pricing scheme, the developer can estimate the monthly cost of using the API:

The free trial offers $18 worth of API calls or approximately 7,200 tokens, whichever comes first.
After the trial, the cost of using the API is $0.003 per token.
Therefore, the estimated monthly cost for the developer’s application would be $30,000 per month (10,000,000 tokens per month * $0.003 per token).

Licenses Cost:

In addition to the API cost, ChatGPT offers licenses for commercial use. Licenses allow users to deploy ChatGPT on their own infrastructure or use it for commercial purposes. The license cost is based on the number of tokens processed and the number of users.

To estimate the cost of using ChatGPT for commercial purposes, developers can use the top-down estimation technique. They can start with an overall budget, divide it among project tasks, and calculate the license cost based on the number of tokens processed and the number of users. The license cost starts at $2,500 per year for up to 10 million tokens and five users, with additional tokens and users available for an extra fee.

Effective Cost Estimation and Price Optimization for ChatGPT API

There are several real-world examples of how companies have used cost estimation and price optimization techniques to improve their profitability.

For instance, Google estimated the cost of developing its search engine using the Bottom-up estimation technique, where the cost of each task was estimated and used to optimize the budget.

Tools offered by Open AI to calculate cost, how tokens work, and estimate your usage

To estimate costs accurately, developers must understand how tokens work and how their usage is tracked.

OpenAI provides a set of tools that developers can use to estimate the cost of using their NLP models, such as Chat GPT and Google BERT. These tools help developers understand how many tokens they will use, how much it will cost, and how to optimize their usage to minimize costs.

1. Tokenizer tool

OpenAI provides an interactive Tokenizer tool that allows developers to experiment with tokenization and estimate the number of tokens that will be used for a given text input. The tool displays the number of tokens in the text input in real-time and helps developers understand how tokenization works.

https://platform.openai.com/tokenizer

2. Usage tracking dashboard

OpenAI also provides a usage tracking dashboard that displays how many tokens have been used during the current and past billing cycles. This dashboard helps developers keep track of their token usage and monitor their costs.

https://platform.openai.com/account/usage

As per official document ChatGPT API Pricing and Billing :

The ChatGPT API and ChatGPT Plus subscription are billed separately.The API has its own pricing, which can be found at https://openai.com/pricing.
The ChatGPT Plus subscription covers usage on chat.openai.com only and costs $20/month.
Completions API : https://platform.openai.com/docs/api-reference/completions

Completions requests are billed based on the number of tokens sent in your prompt plus the number of tokens in the completion(s) returned by the API.

The “best_of” and “n” parameters may also impact costs.

Because these parameters generate multiple completions per prompt, they act as multipliers on the number of tokens returned.

Your request may use up to num_tokens(prompt) + max_tokens * max(n, best_of) tokens, which will be billed at the per-engine rates outlined at the top of the pricing page.

For example, if your prompt contains 10 tokens and you request a single 90 token completion from the davinci engine, your request will use 100 tokens and will cost $0.002.

Developers can limit costs by reducing prompt length or maximum response length, limiting usage of best_of/n, adding appropriate stop sequences, or using engines with lower per-token costs.

Tips :

In the case of ChatGPT API, there are a few tips for effective cost estimation and price optimization that developers can consider:

Choose the right ChatGPT model: The most capable and cost-effective model is gpt-3.5-turbo, which is optimized for chat but also works well for traditional completion tasks. It uses fewer tokens and is 1/10th the cost of text-davinci-003. Developers can experiment with other models to see if they can get the same results with lower latency or cost.https://platform.openai.com/docs/models/gpt-3-5
Reduce the number of tokens used per message: To optimize the price, the developer can consider various techniques, such as Developers can use more concise language or limit the number of messages per conversation to reduce the number of tokens used per message.
Implement caching mechanisms: Developers can reduce the number of API calls made per user by implementing caching mechanisms.They could also consider implementing caching mechanisms to reduce the number of API calls made per user.
Explore volume discounts: Additionally, the developer could explore ChatGPT’s volume discounts, which offer lower prices for higher usage levels.ChatGPT offers volume discounts, which offer lower prices for higher usage levels.Volume discounts refer to the discounted pricing that is offered to customers who use a higher volume of ChatGPT API requests. Essentially, the more tokens a customer uses, the more they can save on the cost per token. For example, if a customer uses 10,000 tokens per month, they may be eligible for a discounted rate compared to a customer who only uses 1,000 tokens per month. These volume discounts can help customers save money on their overall usage of ChatGPT’s API.
Developers can configure a usage hard limit in their billing settings, after which ChatGPT will stop serving their requests. They can also configure a soft limit to receive an email alert once they pass a certain usage threshold. Checking the usage tracking dashboard regularly is recommended to monitor spend.

Overall, by carefully estimating the number of tokens their application will use and implementing optimization techniques, the developer can use ChatGPT’s API in a cost-effective manner.

Reference :