OpenAI API: Its Pricing Model, Determinants & Cost Comparison

TL;DR

• OpenAI API is a versatile tool for developers to integrate advanced AI capabilities into their applications, with a focus on its user-friendly interface suitable even for those with limited NLP knowledge.
• The OpenAI API Pricing Model operates on a Pay-As-You-Go basis, where the cost is determined by API type, request volume, and task complexity, offering flexibility and scalability for all types of users.
• Key factors affecting the cost of using OpenAI's API include the API type, number of requests, complexity of tasks, and the need for integration with other tools, highlighting the need for careful planning and optimization of API usage.
• With OpenAI's API, you can control your expenses through features like setting soft and hard limits on usage, allowing for efficient management of resources and costs.
• Examples of OpenAI API's applications, like ChatGPT for Snapchat's My AI and Quizlet's virtual tutor, illustrate its versatility and real-world utility.
• Comparing OpenAI's API features, costs, and capabilities with other AI APIs help make informed decisions that align with your innovation and creation goals.

We are living in a world where Artificial Intelligence (AI) has penetrated nearly every one of our lives. We could say AI has really reshaped the way the world works, and OpenAI is one organization that is spearheading this revolution. OpenAI’s API offers organizations, individuals, and teams to integrate AI into their services and solutions.

So, for a product so much in demand, how does OpenAI price its API? This blog explains just that. But before that, let’s first get down to the basics.

What is OpenAI’s API and What is it Capable of?

OpenAI is one of the leading organizations involved in AI research. The company’s API is a cloud-based platform allowing developers to access OpenAI’s GPT-3 and other advanced language models they developed.

OpenAI’s API is a multifaceted resource with highly advanced capabilities such as:

• Ability to accurately perform Natural Language Processing tasks
• Automation of text classification and question-answering
• Easy machine translation and text summarization
• Creation of diverse content
• Development of hi-tech conversational AI systems
• Analysis of customer data
• Image recognition

What makes OpenAI’s API unique is its simple and user-friendly interface, which is convenient even for developers with limited NLP (Natural language processing) knowledge. Using the API, developers can integrate their own applications and services with these AI capabilities.

So, how does one decide on a pricing model for such an omnipotent API? Let’s go further into the details.

OpenAI’s Pricing Model: How Does It Work?

OpenAI’s API is based on the Pay-As-You-Go pricing model, where users will pay only for the API requests they use. The PAYG model is already well-known for its many benefits, and in this context, it makes for a cost-effective solution for those wanting to invest in the API.

The PAYG model consists of two key components:

1. Cost per request refers to the fee for each user API request. The determinants of this price are:

• Type of API
• Volume of API requests
• Complexity of the task

2. The monthly quota refers to the maximum number of API requests allowed per month. The quotas can be increased or decreased depending on the PAYG model you choose to go with.

Under the pay-as-you-go pricing strategy, users can scale the API’s usage according to their needs. This agility and scalability will make OpenAI’s API accessible for individuals, large organizations, and startups looking to use it to their advantage without creating a large-scale commitment.

OpenAI’s API Cost: 4 Factors That Determine Its Price

Like other APIs, OpenAI’s API has an exclusive list of factors determining its cost. This list includes:

1. The type of API used.

The cost per request depends mainly on the type of API used. In other words, using a complex API such as an image generation API will cost you more than what you will pay for a text generation API.

For example, the ChatGPT API costs $0.002 for every thousand tokens for the paid version. These tokens are the sequences of messages with metadata consumed by the model. Contrariwise, the audio-based Whisper, is a large V2 model which costs $0.006 for every minute of usage.

2. The number of API requests.

If you opt for a monthly quota, you must be prudent with your API usage, as the more API requests you make, the more you will be charged. OpenAI API's text comparison endpoint, for example, measures relationships between texts based on text-embedding-ada-002. The embedding endpoint charges for every token volume as it offers the following text-related features:

• Recommendations
• Sentiments
• Classifications
• Differences
• Clustering
• Relevance

3. The task complexity.

It goes without saying that complex tasks involving complex AI models will cost more than those requiring simpler versions.

Let’s consider Image Generation from OpenAI’s API. It is one of the most intuitive features based on the DALL.E model. This image generation task involves endpoints capable of creating and editing image variations. These variations are based on natural language prompts. With such complexities involved, the cost of image generation tasks is high.

4.Multiple tool integration

OpenAI's API is more expensive to integrate with other tools like your CRM system. Take ChatGPT API, for example. There are a number of apps that integrate the API to power various features.

Snapchat uses ChatGPT API to enable the My AI feature, which all paid users of SnapChat+ can use. ChatGPT API is also used by Quizlet. The ChatGPT API powers this study aid app’s virtual tutor Q-Chat. Instacart, too, is all set and ready to roll out Ask Instacart. With the help of ChatGPT API, the app will answer all customer-related queries based on product data collected from the company’s retail partners.

Further, the cost also varies depending on the model you are using. Let’s break this down for you.

Also Read: How to Choose the Best SaaS Pricing Consultant

Cost Comparison of OpenAI’s API Engines: How Much Will Each Model Cost You?

ChatGPT, the conversational engine built with OpenAI’s GPT API, has created a frenzy since its launch. If you aim to use this API from OpenAI every single day, you need to know what it will cost you for each API call or text generation request.

OpenAI’s pricing model charges you on the number of processed tokens or word fragments used in NLP. OpenAI charges you for the prompt and the output text at a rate of $0.002/1000 tokens, which is roughly 750 words. So, a prompt containing 150 tokens and an answer containing 850 tokens will cost $0.02 per 1000 tokens. This price is for OpenAI’s DaVinci, one of its most advanced models.

When choosing a GPT-3 model, you need to consider and compare the cost and capabilities of each model to determine what aligns best with your interests.

To compare costs, we take into consideration the four main GPT-3 models:

• DaVinci
• Ada
• Babbage
• Curie

The charge for each model is based on the number of processed tokens, where 1000 tokens are equivalent to approximately 750 words. Based on this concept, the following are the costs you will pay for 1000 tokens:

Source: OpenAI.com - Numbers as of January 2023.

• DaVinci- $0.02
• Curie- $0.002
• Babbage- $0.0005
• Ada- $0.0004

Here, token usage is measured based on the following:

• Price estimation of GPT-3 inputs
• Prompt preparation
• Testing GPT-3 API on various models

In this case, the prompt or instruction given to the model impacts the number of output tokens or responses despite the unclear correlation between the input tokens (prompt + corpora) and the output tokens (response).

The cost of GPT-3 rides mainly on the specific use case. However, there are other determinants, such as:

• The prompt quality wherein a high-quality prompt will give you a more accurate response.
• The GPT-3 model availability- As the demand for the GPT-3 model increases, the availability and price will also increase.
• Customization costs- Adding specific functionalities and development works will cost you more.
• The GPT-3 model temperature- The temperature is a parameter that controls the randomness of the model’s outputs. A high-temperature results in a diverse and unpredictable production, which requires more computational resources for the model to work. The use of these additional resources will impact your costs.

Does that mean there is no choice but to pay a high price for GPT-3? Not really. You can control your expenses by:

• Setting soft limits where you receive an email alert once you cross the usage threshold.
• Setting the maximum tokens parameter in the API request. Setting hard limits to reject subsequent API requests once you’ve reached the threshold.

Thus, with the pay-as-you-go pricing model, you can optimize OpenAI’s API and capitalize on its flexibility and scalability.

The pricing model allows you to conveniently scale up or down per your needs without committing to a monthly subscription fee.

Closing Thoughts

OpenAI will be the launchpad for creators bursting with innovation, creation, and intuition. It may also signal the curtain call for companies with outdated thinking, legacy burdens, hierarchy burdens, and an anti-AI mindset.

In short, OpenAI’s API is a sensible way to move forward. If that’s your plan, you ought to consider and compare its features, costs, and capabilities with other AI APIs out there.

Need help implementing your pricing strategy? Reach out to the Togai team. We will be glad to help you with our expertise.