How Do I Use the OpenAI API and Find the API Key? Step by Step Guide for 2026

AI technology has steadily become more powerful in recent years and is poised to transform even more industries in the future. According to recent reports, the global AI market will be worth more than $1.5 trillion by 2030. A PwC global AI study also shows that global GDP could grow by $15.7 trillion by 2030, with China and North America accounting for the biggest economic gains thanks to AI technology.

Recently, OpenAI, one of the leading AI research organizations in the world, released powerful APIs that allow developers to access advanced AI models. Unlike many AI systems that are designed for a single use case, the OpenAI API can be used across a wide range of tasks.

Read on as we break down everything you need to know about the OpenAI API, what it does, and how to use it properly.

Key Insights

• OpenAI API = cloud interface to pretrained AI models. Provides programmatic access to language, image, speech, and embedding models so developers can send inputs (text/audio/images) and receive AI-generated outputs.
• Primary purpose: integrate AI into software systems. Used for chatbots, content generation, semantic search, summarization, coding assistants, and automation inside apps, websites, and enterprise tools.
• Basic workflow: create OpenAI account → generate API key → install SDK (`pip install openai` or `npm install openai`) → send request to model endpoint → receive generated response.
• Pricing model: pay-as-you-go based on tokens. Tokens ≈ text units processed by the model; larger models cost more but provide stronger reasoning and multimodal capabilities.
• Main model categories: GPT models (text/multimodal reasoning), Whisper (speech-to-text), image generation models (e.g., DALL-E), and embedding models (vector representations for search/similarity).

What is OpenAI API?

The OpenAI API is a cloud-based interface that gives users access to pre-trained AI models developed by OpenAI. These models include large language models, image generation models, speech recognition systems, and embedding models.

The API allows developers to integrate advanced AI capabilities into their applications, products, and services. Unlike traditional AI tools that are designed for one specific task, the OpenAI API provides a flexible platform where developers can send input (such as text, images, or audio) and receive intelligent outputs generated by AI models.

Any programming language or application can use the OpenAI API for various purposes, including semantic search, content generation, translation, sentiment analysis, summarization, and many other tasks.

Once you provide the API with a prompt or input, the model processes the request and returns a response that matches the instructions given.

It’s also worth noting that developers can guide the behavior of the models by providing examples or instructions within the prompt. The success of the results often depends on how clearly the task is described.

Looking for innovative solutions?
Addepto is a Generative AI development company that can help you transform your business with cutting-edge technologies.

How to use the OpenAI API?

Using the OpenAI API is simple and straightforward. To get started, ensure you follow these steps.

Create an OpenAI account

If you don’t already have an OpenAI account, you need to create one by following the steps on the OpenAI website.

In Python development, you can install the OpenAI package using pip:

pip install openai

If you are using Node.js, you can install the package using npm:

npm install openai

After that, enter your email address and password to log in to your OpenAI account dashboard.

Generate the OpenAI API key

Once you’ve created your OpenAI account or logged into an existing one, you will see your profile icon in the top-right corner of the dashboard.

To generate an OpenAI API key, click your profile icon and select “View API keys.”

You will see an option called “Create new secret key.”

If you don’t already have an API key, click this option to generate one. Make sure you store this key securely, as the full key will only be shown once.

The API key is required to authenticate your application when sending requests to OpenAI models.

Make a test call with the OpenAI API key

Using your OpenAI API key, you can make a simple request to one of the available model endpoints to test the connection.

This can be done using a server-side programming language such as JavaScript (Node.js) or Python.

For example:

from openai import OpenAI

client = OpenAI(api_key="YOUR_API_KEY")

response = client.responses.create(
    model="gpt-4.1-mini",
    input="Explain artificial intelligence in simple terms."
)

print(response.output_text)

After successfully authenticating your API key and receiving a response from the model, you can integrate the API into your application’s backend and build your user interface around it.

Is the OpenAI API free?

You can create an OpenAI account and obtain an API key without paying upfront. In some cases, new users may receive limited trial credits to experiment with the API.

However, OpenAI API generally operates on a pay-as-you-go pricing model. This means you pay only for the resources you use.

Pricing is typically based on the number of tokens processed by the model.

Tokens are pieces of text that the model processes. In English text, 1,000 tokens are roughly equivalent to about 750 words, although this can vary depending on the language.

The cost depends on the model being used and the number of tokens processed. Smaller and more efficient models are designed to be more cost-effective, while larger models provide more advanced reasoning capabilities.

Image generation models and speech processing models may use different pricing structures based on factors such as image resolution or audio duration.

In many cases, using the OpenAI API can be more cost-efficient for applications than using a subscription-based AI tool, depending on how frequently the system is used.

How to get the OpenAI API key?

To obtain the OpenAI API key, you can follow these steps:

1. Create an OpenAI account: If you don’t already have an OpenAI account, navigate to the OpenAI website and sign up by clicking the “Sign Up” button.
2. Verify your account: After signing up, you will receive an email from OpenAI to confirm your account. Open this email and click the verification link.
3. Log in: Return to the OpenAI website and click the “Log In” button. Enter your email address and password.
4. Access API keys: Once logged in, click on your profile icon and select “View API keys.”
5. Generate a new API key: In the API keys section, click the button labeled “Create new secret key.”
6. Name your key: A window will appear asking you to name your API key so you can easily identify its purpose.
7. Save your key securely: Copy the generated key and store it in a secure place such as an environment variable or secret manager.
8. Set usage limits (optional): To control your monthly spending, you can set usage limits in the dashboard.
9. Billing setup: If you plan to use the API beyond the free trial credits, add a payment method in the billing section.
10. Security reminder: Keep your API key secure and never expose it in public repositories or client-side code.

Types of OpenAI API models

The OpenAI API provides access to a wide selection of models with different capabilities and performance characteristics.

Here are some of the main categories of OpenAI API models.

GPT models

GPT models are natural language processing models designed to understand and generate human-like text.

These models are trained on large datasets and can perform tasks such as copywriting, summarization, classification, translation, and answering questions.

Modern GPT models include:

• GPT-4o – a powerful multimodal model capable of processing text, images, and audio
• GPT-4.1 – an advanced model designed for complex reasoning tasks
• GPT-4.1 mini – a smaller, faster, and more cost-efficient model for high-volume applications

These models are widely used in chatbots, writing assistants, automation tools, and business intelligence systems.

Read more about GPT-4 vs GPT-3: Main Differences

Speech recognition (Whisper)

Whisper is an automatic speech recognition (ASR) system trained to convert audio into text. This model was trained on several hours’ worth of audio datasets collected from the web. It is also capable of performing other tasks, such as language detection, multilingual transcription, and speech translation.

You can use the OpenAI Whisper as a voice assistant, speech translator to English, and chatbot. You can also use the OpenAI model to transcribe real-time speech into subtitles and to take notes during meetings. If you have a working knowledge of Python language, you can always integrate Whisper into your applications. It’s worth noting that Whisper can transcribe speech in 99 languages and translate them into English.

The endpoint usage of Whisper API is simple. All you need to do is feed the Whisper model with audio, then opt for the Openai.Audio. Transcribe or Openai.Audio. Translate option to transcribe or translate it respectively. It’s worth noting that both the translate and transcribe endpoints can only accommodate an audio file of up to 25MB. Fortunately, both endpoints support the most popular types of audio files, including m4a, mp3, mp4, wav, MPEG, MPGA, and webm.

Image generation models

OpenAI also provides models capable of generating images from natural language descriptions.

These models allow users to create high-quality visuals by simply describing the desired image in text.

Image generation models are commonly used for:

• marketing and advertising visuals
• product concept art
• game development assets
• design prototyping
• creative projects

Users can control style, composition, and image resolution through prompts and parameters.

DALL-E

This state-of-the-art generative AI technology allows users to create high-resolution images with text. This OpenAI API is capable of generating entirely new images in various styles as specified by a user’s prompts. The name ‘DALL-E’ is a blend of Spanish artist Salvador Dalli and the Disney WALL-E movie.

DALL-E mainly relies on deep learning models and the GPT-3 API natural language processing model to understand natural language prompts and create new images.

OpenAI built DALL-E using a subset of the GPT-3 API large language model. However, instead of using the entire 175 billion parameters provided by the GPT-3 API, DALL-E only uses about 12 billion parameters.

To prove that DALL-E was capable of correctly generating high-resolution images, OpenAI built the Contrastive Language-Image Pre-Training (CLIP) model. The CLIP model was trained using 400 million labeled images. Afterward, OpenAI used CLIP to train DALL-E and determine the ideal captions for generated images.

Embeddings

Embeddings are a selection of models that convert text into numerical forms. An embedding model is usually used to compare the relationship between two pieces of text. The embedding API uses the text-embedding-ada-002 model, to determine the relationship between two texts based on the distance between two vector points. The narrower the distance, the more related the texts under comparison are.

Even though OpenAI says you can use first-generation embedding models for your tasks, you should know that the newer models are cheaper and perform better. OpenAI has also come forward to warn users that first-generation models might show a certain degree of bias towards certain people.

What is ChatGPT?

ChatGPT is a conversational AI application built on top of OpenAI’s language models.

Unlike the OpenAI API, which is designed for developers, ChatGPT provides a user-friendly interface that allows people to interact with AI through natural conversation.

One of the reasons ChatGPT became so popular is that it can maintain the context of an ongoing conversation. This allows users to ask follow-up questions and interact with the AI in a more natural way.

Many of the capabilities available in ChatGPT are powered by the same underlying models that developers can access through the OpenAI API.

It might be interesting for you: How can you use ChatGPT in business?

Can I use OpenAI API for commercial purposes?

Yes, you can use content generated by OpenAI models for commercial purposes such as products, services, and publications, as long as you comply with OpenAI’s terms of service and applicable laws.

However, you remain responsible for ensuring that the generated content does not violate legal requirements or platform policies.

Wrapping up

OpenAI APIs offer a wide variety of benefits for developers and organizations looking to integrate AI technology into their applications.

Whether you want to build a custom AI solution that generates text, analyzes data, creates images, or processes speech, OpenAI provides APIs that can support these capabilities.

Businesses of all sizes can use OpenAI technology to automate repetitive tasks, improve customer service, and build intelligent systems that process large volumes of information.

As AI technology continues to evolve, OpenAI’s models and APIs are expected to become even more powerful and accessible for developers around the world.

The article is an updated version of the publication from May 3, 2023. It was recently updated on March 16, 2026, to incorporate new ChatGPT models, statistics, and key insights.

References

1. Statistica.com. AI Market Size Revenue Comparisons. URL: https://www.statista.com/statistics/941835/artificial-intelligence-market-size-revenue-comparisons/. Accessed May 11, 2023
2. PWC.com. AI Study. URL: https://www.pwc.com/gx/en/issues/data-and-analytics/publications/artificial-intelligence-study.html. Accessed May 11, 2023
3. Github.com. OpenAI Python. URL: https://github.com/openai/openai-python. Accessed May 11, 2023
4. Github.com. OpenAI-Node. URL: https://github.com/openai/openai-node. Accessed May 11, 2023
5. Labs.openai.com. Waitlist. URL: https://labs.openai.com/waitlist. Accessed May 11, 2023
6. Openai.com. Pricing. URL: https://openai.com/pricing, Accessed May 11, 2023
7. Platform.openai.com. Code Completion. URL: https://platform.openai.com/docs/guides/code. Accessed May 11, 2023
8. Slator.com. How Big Of a Deal is Whisper for ASR Multilingual Transcription. URL: https://slator.com/how-big-a-deal-is-whisper-for-asr-multilingual-transcription/.
9. Openai.com. URL: https://openai.com/research/clip/. Accessed May 11,2023