Who Invented ChatGPT

ChatGPT was first introduced by OpenAI in 2020 as a successor to the previous generation of GPT models. GPT stands for “Generative Pre-trained Transformer,” a type of neural network architecture that has been widely used in NLP. The GPT model was originally introduced by OpenAI in 2018 and has undergone several iterations since then.

The development of ChatGPT involved a large team of researchers and engineers at OpenAI, who trained the model using a massive dataset of natural language text. The training data for ChatGPT included a wide range of sources, including books, articles, and online content. The model was trained using a technique called unsupervised learning, which means that it was not explicitly taught to perform any specific task, but rather learned to generate responses to natural language queries by analyzing patterns in the training data.

How Much Data Is Used to Train ChatGPT

One of the key factors contributing to the success of ChatGPT is the massive amount of data that was used to train the model. The training data for ChatGPT consisted of a diverse range of sources, including books, articles, and online content. In total, the model was trained using over 45 terabytes of text data, which is equivalent to over 800 billion words.

The data used to train ChatGPT was carefully selected to ensure that the model was exposed to a wide range of linguistic patterns and structures. The training data included text from a variety of genres and styles, including fiction, non-fiction, news articles, and academic papers. This helped to ensure that the model was capable of generating responses to a wide range of natural language queries.

The training process for ChatGPT involved a technique called unsupervised learning, which means that the model was not explicitly taught to perform any specific task. Instead, it learned to generate responses to natural language queries by analyzing patterns in the training data. This approach allowed the model to develop a deep understanding of language, and to generate contextually relevant responses to a wide range of queries.

The sheer volume of data used to train ChatGPT was a significant factor in its success, as it allowed the model to learn from a vast and diverse range of linguistic patterns and structures. This helped to ensure that the model was capable of generating coherent and contextually relevant responses to a wide range of queries. As the field of natural language processing continues to evolve, it is likely that even larger and more diverse datasets will be used to train future language models, leading to even more advanced AI systems.

The evolution of natural language processing (NLP), from GPT-1 to GPT-4

The evolution of natural language processing (NLP) models over the past decade has been nothing short of remarkable. From simple language models that struggled to understand basic queries to sophisticated models that can generate coherent and contextually relevant responses to complex questions, NLP has come a long way in a short time.

One of the key players in this evolution has been OpenAI, a research organization that has been at the forefront of developing some of the most advanced NLP models in the world. In this article, we will take a chronological look at the development of these models, culminating with the latest and greatest model: GPT-4.

GPT-1: The Beginning of a New Era

In 2018, OpenAI released the first version of their language model, the Generative Pre-trained Transformer (GPT-1). This model was trained on a large corpus of text from the internet, and was capable of generating coherent and grammatically correct sentences. It quickly became clear that this was a major step forward in the field of NLP, and sparked a flurry of research activity in the area.

GPT-1 was not perfect, however. While it was capable of generating coherent sentences, it struggled to understand context and was prone to generating irrelevant or nonsensical responses to certain queries. Nevertheless, it was a significant breakthrough in the field, and set the stage for even more advanced models to come.

GPT-2: Bigger, Better, and More Capable

In 2019, OpenAI released the second version of their language model, GPT-2. This model was trained on an even larger corpus of text than GPT-1, and was capable of generating longer, more complex sentences. It also introduced the concept of “few-shot learning,” which allowed the model to adapt to new tasks with just a few examples.

One of the key features of GPT-2 was its ability to generate text that was almost indistinguishable from human-written text. This led to concerns about the potential for the model to be used for malicious purposes, such as generating fake news or impersonating individuals. As a result, OpenAI initially decided not to release the full version of the model to the public.

GPT-3: A Giant Leap Forward

In 2020, OpenAI released their most advanced language model yet: GPT-3. This model was trained on an even larger corpus of text than its predecessors, and was capable of generating incredibly complex and contextually relevant responses to a wide range of queries. It also introduced the concept of “zero-shot learning,” which allowed the model to perform tasks that it had not been explicitly trained to do.

One of the most impressive features of GPT-3 was its ability to generate text that was almost indistinguishable from human-written text. This led to a surge of interest in the model, and sparked a wave of research activity in the area of NLP.

GPT-4: The Next Evolution

As of 2023, OpenAI has not yet officially released GPT-4, but the organization has provided some details about the model and its capabilities. According to OpenAI, GPT-4 has been developed to improve model “alignment,” which is the ability to follow user intentions while also making it more truthful and generating less offensive or dangerous output.

In terms of performance, GPT-4 improves on GPT-3.5 models regarding the factual correctness of answers. The number of “hallucinations,” where the model makes factual or reasoning errors, is lower, with GPT-4 scoring 40% higher than GPT-3.5 on OpenAI’s internal factual performance benchmark.

Another improvement is in the model’s adherence to guardrails. If you ask it to do something illegal orunsavory, it is better at refusing the request. GPT-4 also improves “steerability,” which is the ability to change its behavior according to user requests. For example, you can command it to write in a different style or tone or voice.

One major change in GPT-4 is its ability to use image inputs (research preview only; not yet available to the public) and text. Users can specify any vision or language task by entering interspersed text and images. Examples showcased highlight GPT-4 correctly interpreting complex imagery such as charts, memes, and screenshots from academic papers.

OpenAI evaluated GPT-4 by simulating exams designed for humans, such as the Uniform Bar Examination and LSAT for lawyers, and the SAT for university admission. The results showed that GPT-4 achieved human-level performance on various professional and academic benchmarks.

OpenAI also evaluated GPT-4 on traditional benchmarks designed for machine learning models, where it outperformed existing large language models and most state-of-the-art models that may include benchmark-specific crafting or additional training protocols.

OpenAI tested GPT-4’s capability in other languages by translating the MMLU benchmark, a suite of 14,000 multiple-choice problems spanning 57 subjects, into various languages using Azure Translate. In 24 out of 26 languages tested, GPT-4 outperformed the English-language performance of GPT-3.5 and other large language models.

Overall, GPT-4 represents a significant step forward in the field of NLP. It addresses many of the shortcomings of previous models, such as their tendency to generate irrelevant or nonsensical responses to certain queries. With its improved performance, GPT-4 has the potential to revolutionize a wide range of industries, from customer service to content creation to scientific research.

As with previous models, GPT-4 is not without its limitations. One major concern is the potential for the model to be used for malicious purposes, such as generating fake news or impersonating individuals. OpenAI has taken steps to address this issue, such as limiting access to the model and introducing guardrails to prevent it from generating offensive or dangerous content.

Despite these concerns, the development of GPT-4 represents a major achievement in the field of NLP. With its improved performance and new capabilities, it has the potential to drive even more innovation and research in this rapidly evolving field. As researchers continue to push the boundaries of what is possible with NLP models, it will be exciting to see what the future holds for this technology.

ChatGPT Price and Availability

Is ChatGPT Free to Use?

OpenAI offers both free and paid access to ChatGPT. The free access provides a basic level of interaction with the AI, while paid subscriptions offer more features and resources.

ChatGPT Professional

ChatGPT Professional is a subscription plan designed for users who require advanced features, faster response times, and priority access to new updates. The pricing details can be found on OpenAI’s website. In reality, we are speaking about ChatGPT Plus.

There is no specific “ChatGPT Professional” subscription plan. However, there is a “ChatGPT Plus” subscription plan, which I have already described in a previous response.

Please note that OpenAI may introduce new subscription plans or services in the future that I may not be aware of. It is always a good idea to visit the official OpenAI website for the latest information on available plans and services.

ChatGPT Plus

ChatGPT Plus is a subscription plan offered by OpenAI that provides users with enhanced access to the ChatGPT model. By subscribing to ChatGPT Plus, users can enjoy a range of benefits compared to the basic free access, including:

1. Faster Response Times: Subscribers can expect quicker interactions with the ChatGPT model, making it more convenient and efficient for various use cases.
2. General Access: ChatGPT Plus ensures users have continuous access to the model, even during peak times when demand is high.
3. Priority Access to New Features and Improvements: Subscribers receive priority access to any new features, updates, or improvements made to the ChatGPT model, allowing them to take advantage of the latest advancements in AI technology.

ChatGPT Plus is designed for users who seek an enhanced experience with ChatGPT, whether for personal or professional purposes. By offering additional benefits, it caters to those who require more resources, faster interactions, and priority access to stay ahead in the rapidly evolving world of AI-driven applications. The price of chatGPT plus is about 20$ a month. 

ChatGPT API

OpenAI provides an API for developers who want to integrate ChatGPT into their applications, products, or services. Pricing and usage details for the ChatGPT API can be found on the OpenAI website.

How to Generate Your ChatGPT API Key ?

To generate your ChatGPT API key, follow these simple steps:

1. Sign up: First, create an account on the OpenAI website (https://www.openai.com) if you haven’t already.
2. Access the API dashboard: After you’ve logged in, navigate to the API dashboard. You can usually find this in the user menu or by visiting a direct link, such as https://platform.openai.com/signup.
3. Review the documentation: Familiarize yourself with the API documentation provided by OpenAI. This will give you a better understanding of the API’s capabilities, usage limits, and pricing. The documentation can be found at https://beta.openai.com/docs.
4. Request API access: Some services might require you to request API access explicitly. If needed, fill out the necessary forms or contact OpenAI’s support to gain access to the ChatGPT API.
5. Generate your API key: Once you have access, look for the option to generate an API key in the API dashboard. This is typically done by clicking a button labeled “Create API Key” or something similar. A unique API key will be generated for you, which you’ll need to save securely.
6. Integrate the API key into your application: Use the API key to authenticate your requests when interacting with the ChatGPT API in your application. Follow the guidelines provided in the API documentation to ensure proper implementation.

Remember to keep your API key confidential and secure, as it grants access to your account and any associated usage limits or charges. If you believe your API key has been compromised, generate a new one and update your application accordingly.

# Sample code for developing a Chatbot using ChatGPT
import openai
openai.api_key = "YOUR_API_KEY"
response = openai.Completion.create(
  engine="davinci",
  prompt="Hello, how can I assist you today?",
  max_tokens=100
)
print(response.choices[0].text)

# Sample code for developing a Virtual Assistant using ChatGPT
import openai
openai.api_key = "YOUR_API_KEY"
response = openai.Completion.create(
  engine="davinci",
  prompt="Can you schedule an appointment for me at 2pm on Friday?",
  max_tokens=100
)
print(response.choices[0].text)

# Sample code for developing a Customer Support tool using ChatGPT
import openai
openai.api_key = "YOUR_API_KEY"
response = openai.Completion.create(
  engine="davinci",
  prompt="I have an issue with my order, can you help me?",
  max_tokens=100
)
print(response.choices[0].text)

# Sample code for developing a Language Translation tool using ChatGPT
import openai
openai.api_key = "YOUR_API_KEY"
response = openai.Completion.create(
  engine="davinci",
  prompt="Translate 'Hello, how are you?' to French",
  max_tokens=100
)
print(response.choices[0].text)

ChatGPT Applications for Content Creation

ChatGPT can be used to generate content, such as articles, blog posts, and product descriptions, based on a given topic or keyword.

# Sample code for generating Content using ChatGPT
import openai
openai.api_key = "YOUR_API_KEY"
response = openai.Completion.create(
  engine="davinci",
  prompt="Write an article about the benefits of exercise",
  max_tokens=1000
)
print(response.choices[0].text)

ChatGPT Applications for Personalized Marketing

ChatGPT can be used to personalize marketing messages and campaigns, by generating targeted content that resonates with individual customers.

# Sample code for generating Personalized Marketing messages using ChatGPT
import openai
openai.api_key = "YOUR_API_KEY"
response = openai.Completion.create(
  engine="davinci",
  prompt="Write a personalized email to John about our new product",
  max_tokens=500
)
print(response.choices[0].text)

ChatGPT Applications for Mental Health

ChatGPT can be used to develop mental health applications, like chatbots and virtual assistants, that can provide emotional support and assistance to individuals.

# Sample code for developing a Mental Health tool using ChatGPT
import openai
openai.api_key = "YOUR_API_KEY"
response = openai.Completion.create(
  engine="davinci",
  prompt="I'm feeling anxious, can you help me?",
  max_tokens=100
)
print(response.choices[0].

ChatGPT Applications for Educational Tools

ChatGPT can be used to develop educational tools that provide personalized learning experiences to students, by generating quizzes, exercises, and study materials.

# Sample code for developing an Educational tool using ChatGPT
import openai
openai.api_key = "YOUR_API_KEY"
response = openai.Completion.create(
  engine="davinci",
  prompt="Create a quiz about the Solar System",
  max_tokens=500
)
print(response.choices[0].text)

ChatGPT Applications for Creative Writing

ChatGPT can be used to assist with creative writing tasks, like generating plot ideas, character descriptions, and dialogue.

# Sample code for Creative Writing using ChatGPT
import openai
openai.api_key = "YOUR_API_KEY"
response = openai.Completion.create(
  engine="davinci",
  prompt="Generate a story plot about a detective who solves a mystery",
  max_tokens=500
)
print(response.choices[0].text)

ChatGPT Applications for Legal Research

ChatGPT can be used to assist with legal research tasks, like identifying relevant cases, statutes, and legal arguments.

# Sample code for Legal Research using ChatGPT
import openai
openai.api_key = "YOUR_API_KEY"
response = openai.Completion.create(
  engine="davinci",
  prompt="What is the statute of limitations for personal injury cases in California?",
  max_tokens=100
)
print(response.choices[0].text)

ChatGPT Applications for Medical Diagnosis

ChatGPT can be used to develop medical diagnosis tools that can analyze patient symptoms and provide preliminary diagnoses.

# Sample code for Medical Diagnosis using ChatGPT
import openai
openai.api_key = "YOUR_API_KEY"
response = openai.Completion.create(
  engine="davinci",
  prompt="What could be causing my headaches and fatigue?",
  max_tokens=100
)
print(response.choices[0].text)

ChatGPT Applications for E-commerce

ChatGPT can be used to enhance e-commerce experiences, by generating personalized product recommendations, improving search results, and providing customer support.

# Sample code for enhancing E-commerce using ChatGPT
import openai
openai.api_key = "YOUR_API_KEY"
response = openai.Completion.create(
  engine="davinci",
  prompt="What are the best shoes for running?",
  max_tokens=100
)
print(response.choices[0].text)

ChatGPT Applications for News Article Generation

ChatGPT can be used to generate news articles based on a given topic, by summarizing relevant information and writing clear and concise articles.

# Sample code for generating News Articles using ChatGPT
import openai
openai.api_key = "YOUR_API_KEY"
response = openai.Completion.create(
  engine="davinci",
  prompt="Write an article about the latest developments in artificial intelligence",
  max_tokens=1000
)
print(response.choices[0].text)

ChatGPT Applications for Personal Finance

ChatGPT can be used to develop personal finance tools, like budgeting and investment advice, based on individual user data.

# Sample code for developing Personal Finance tools using ChatGPT
import openai
openai.api_key = "YOUR_API_KEY"
response = openai.Completion.create(
  engine="davinci",
  prompt="How can I save money on my monthly expenses?",
  max_tokens=100
)
print(response.choices[0].text)

ChatGPT Applications for Gaming

ChatGPT can be used to create interactive gaming experiences, like text-based adventure games, that respond to player actions and decisions.

# Sample code for creating a Text-Based Adventure Game using ChatGPT
import openai
openai.api_key = "YOUR_API_KEY"
response = openai.Completion.create(
  engine="davinci",
  prompt="You are standing in front of a castle. What do you do?",
  max_tokens=100
)
print(response.choices[0].text)

ChatGPT Applications for Travel Planning

ChatGPT can be used to assist with travel planning, by generating personalized itineraries, recommending activities, and answering questions.

# Sample code for Travel Planning using ChatGPT
import openai
openai.api_key = "YOUR_API_KEY"
response = openai.Completion.create(
  engine="davinci",
  prompt="What are some must-see attractions in Paris?",
  max_tokens=100
)
print(response.choices[0].text)

ChatGPT Applications for HR Recruitment

ChatGPT can be used to assist with HR recruitment tasks, like identifying qualified candidates, scheduling interviews, and conducting initial screenings.

# Sample code for HR Recruitment using ChatGPT
import openai
openai.api_key = "YOUR_API_KEY"
response = openai.Completion.create(
  engine="davinci",
  prompt="Can you schedule an interview with John for next week?",
  max_tokens=100
)
print(response.choices[0].text)

ChatGPT Applications for Social Media Management

ChatGPT can be used to enhance social media management, by generating engaging content, analyzing trends, and providing customer support.

# Sample code for Social Media Management using ChatGPT
import openai
openai.api_key = "YOUR_API_KEY"
response = openai.Completion.create(
  engine="davinci",
  prompt="What are some trending topics on Twitter right now?",
  max_tokens=100
)
print(response.choices[0].text)

ChatGPT Applications for Business Intelligence

ChatGPT can be used to analyze business data, generate reports, and provide insights that can help improve decision-making.

# Sample code for Business Intelligence using ChatGPT
import openai
openai.api_key = "YOUR_API_KEY"
response = openai.Completion.create(
  engine="davinci",
  prompt="What are the top-selling products in our online store?",
  max_tokens=100
)
print(response.choices[0].text)

ChatGPT Applications for Resume Writing

ChatGPT can be used to assist with resume writing tasks, like generating job descriptions, highlighting relevant skills, and providing feedback.

# Sample code for Resume Writing using ChatGPT
import openai
openai.api_key = "YOUR_API_KEY"
response = openai.Completion.create(
  engine="davinci",
  prompt="How can I highlight my skills and experience on my resume?",
  max_tokens=100
)
print(response.choices[0].text)

ChatGPT Applications for Speech Recognition

ChatGPT can be used to develop speech recognition tools that can transcribe spoken words into text.

# Sample code for Speech Recognition using ChatGPT
import openai
openai.api_key = "YOUR_API_KEY"
response = openai.Completion.create(
  engine="davinci",
  prompt="What did the speaker say?",
  max_tokens=100
)
print(response.choices[0].text)

ChatGPT Applications for Smart Home Devices

ChatGPT can be used to develop smart home devices, like voice assistants, that can control various appliances and perform tasks based on voice commands.

# Sample code for Smart Home Devices using ChatGPT
import openai
openai.api_key = "YOUR_API_KEY"
response = openai.Completion.create(
  engine="davinci",
  prompt="Turn on the lights in the living room",
  max_tokens=100
)
print(response.choices[0].text)

ChatGPT Applications for Customer Service

ChatGPT can be used to improve customer service experiences, by answering frequently asked questions, resolving issues, and providing personalized recommendations.

# Sample code for Customer Service using ChatGPT
import openai
openai.api_key = "YOUR_API_KEY"
response = openai.Completion.create(
  engine="davinci",
  prompt="What is the status of my order?",
  max_tokens=100
)
print(response.choices[0].text)

ChatGPT Applications for Mental Health

ChatGPT can be used to develop mental health tools that can provide personalized advice, therapy, and support to individuals.

# Sample code for Mental Health using ChatGPT
import openai
openai.api_key = "YOUR_API_KEY"
response = openai.Completion.create(
  engine="davinci",
  prompt="I'm feeling anxious and stressed. What can I do to feel better?",
  max_tokens=100
)
print(response.choices[0].text)

ChatGPT Applications for Personalized Nutrition

ChatGPT can be used to develop personalized nutrition plans, by analyzing individual health data, dietary restrictions, and preferences.

# Sample code for Personalized Nutrition using ChatGPT
import openai
openai.api_key = "YOUR_API_KEY"
response = openai.Completion.create(
  engine="davinci",
  prompt="What are some healthy meals I can make with chicken and vegetables?",
  max_tokens=100
)
print(response.choices[0].text)

ChatGPT Applications for Sports Analytics

ChatGPT can be used to analyze sports data, provide game predictions, and generate player performance reports.

# Sample code for Sports Analytics using ChatGPT
import openai
openai.api_key = "YOUR_API_KEY"
response = openai.Completion.create(
  engine="davinci",
  prompt="What are the chances of the Lakers winning their next game?",
  max_tokens=100
)
print(response.choices[0].text)

ChatGPT Applications for Virtual Personal Assistants

ChatGPT can be used to develop virtual personal assistants that can perform a variety of tasks, like scheduling appointments, making reservations, and sending emails.

# Sample code for Virtual Personal Assistants using ChatGPT
import openai
openai.api_key = "YOUR_API_KEY"
response = openai.Completion.create(
  engine="davinci",
  prompt="Can you schedule a meeting with John for next Monday?",
  max_tokens=100
)
print(response.choices[0].text)

ChatGPT Applications for Virtual Medical Assistants

ChatGPT can be used to develop virtual medical assistants that can answer health-related questions, schedule appointments, and provide basic medical advice.

# Sample code for Virtual Medical Assistants using ChatGPT
import openai
openai.api_key = "YOUR_API_KEY"
response = openai.Completion.create(
  engine="davinci",
  prompt="What are the symptoms of COVID-19?",
  max_tokens=100
)
print(response.choices[0].text)

ChatGPT Applications for Image Captioning

ChatGPT can be used to develop image captioning tools that can automatically generate descriptive captions for images.

# Sample code for Image Captioning using ChatGPT
import openai
openai.api_key = "YOUR_API_KEY"
response = openai.Completion.create(
  engine="davinci",
  prompt="Describe the contents of this image.",
  max_tokens=100
)
print(response.choices[0].text)

ChatGPT Ask Result Vs. Google Search Result

While both ChatGPT and Google Search provide answers to user queries, their underlying mechanisms differ significantly. Google Search relies on indexing web pages and using algorithms to rank the most relevant results. In contrast, ChatGPT generates answers based on its pre-training and understanding of natural language, simulating a human-like conversation.

Why Is ChatGPT so Good?

ChatGPT excels due to its advanced GPT-4 architecture, massive training data, and ability to capture context. These factors enable it to generate coherent, contextually relevant, and human-like responses to a wide range of inputs.

ChatGPT is highly regarded for several reasons, which contribute to its impressive performance in generating human-like text and understanding natural language:

1. Advanced Architecture: ChatGPT is built on the GPT-4 architecture, a state-of-the-art natural language processing technology that enables it to capture complex patterns and relationships between tokens.
2. Massive Training Data: The model is trained on vast amounts of text data from diverse sources, providing it with a broad understanding of language patterns, context, and content.
3. Transfer Learning: ChatGPT is pre-trained on a wide variety of text sources, allowing it to excel in multiple tasks without requiring extensive fine-tuning.
4. Contextual Understanding: With its context window, ChatGPT can generate coherent and contextually relevant responses by incorporating information from previous tokens.
5. Adaptability: The model can adapt to different writing styles, tones, and contexts, making it suitable for a wide array of applications.

These factors combine to make ChatGPT an exceptional AI language model, capable of delivering high-quality and contextually appropriate text generation across various domains.

The Limitations of ChatGPT

Despite its impressive capabilities, ChatGPT has certain limitations that users should be aware of:

1. Plausible but Incorrect Answers: ChatGPT may generate responses that sound reasonable but are factually incorrect or nonsensical. It can be challenging for the model to verify the accuracy of the information it generates.
2. Sensitivity to Input Phrasing: The model’s responses can vary depending on the phrasing of the input. Slight changes in how a question or prompt is presented might lead to different answers.
3. Verbose and Redundant Output: ChatGPT may generate overly verbose or repetitive text, overusing certain phrases or providing more information than necessary.
4. Lack of Consistency: The model may produce inconsistent answers when asked the same or similar questions multiple times. It may not always provide a coherent narrative or maintain consistency throughout longer conversations.
5. Inherent Bias: ChatGPT can inadvertently learn and perpetuate biases present in the training data. This may lead to biased or potentially offensive content generation.
6. Limited Context: While ChatGPT can capture context within a certain window, it may struggle to understand or reference information beyond that window, leading to a loss of context in longer interactions.

Being aware of these limitations can help users set realistic expectations and make informed decisions when integrating ChatGPT into their applications or using it for various tasks.

ChatGPT Pricing

Please note that this table is for illustrative purposes only, and you should consult the official OpenAI website or our article on this topic for the most accurate and current pricing information.

Language Models:

GPT-4: With broad general knowledge and domain expertise, GPT-4 can follow complex instructions in natural language and solve difficult problems with accuracy.

• 8K context: $0.03 / 1K tokens
• 32K context: $0.06 / 1K tokens

ChatGPT: ChatGPT models are optimized for dialogue.

• gpt-3.5-turbo: $0.002 / 1K tokens

InstructGPT: Instruct models are optimized to follow single-turn instructions.

• Ada: Fastest, $0.0004 / 1K tokens
• Babbage: $0.0005 / 1K tokens
• Curie: $0.0020 / 1K tokens
• Davinci: Most powerful, $0.0200 / 1K tokens

Fine-tuning models: Create your own custom models by fine-tuning our base models with your training data.

• Ada: Training $0.0004 / 1K tokens, Usage $0.0016 / 1K tokens
• Babbage: Training $0.0006 / 1K tokens, Usage $0.0024 / 1K tokens
• Curie: Training $0.0030 / 1K tokens, Usage $0.0120 / 1K tokens
• Davinci: Training $0.0300 / 1K tokens, Usage $0.1200 / 1K tokens

Embedding models: Build advanced search, clustering, topic modeling, and classification functionality with our embeddings offering.

• Ada: $0.0004 / 1K tokens

Other models:

Image models: Build DALL·E directly into your apps to generate and edit novel images and art.

• 1024×1024: $0.020 / image
• 512×512: $0.018 / image
• 256×256: $0.016 / image

Audio models: Whisper can transcribe speech into text and translate many languages into English.

• Whisper: $0.006 / minute (rounded to the nearest second)

Usage quotas:

When you sign up, you’ll be granted an initial spend limit, or quota, and we’ll increase that limit over time as you build a track record with your application. If you need more tokens, you can always request a quota increase.

Simple and flexible:

• Start for free: Start experimenting with $5 in free credit that can be used during your first 3 months.
• Pay as you go: To keep things simple and flexible, pay only for the resources you use.
• Choose your model: Use the right model for the job. We offer a spectrum of capabilities and price points.

Always consult the official OpenAI website for the most accurate and up-to-date pricing information on ChatGPT and related services.

Try ChatGPT For Free Now

To experience the power of ChatGPT, you can try it for free by visiting OpenAI’s website.

Sign up for a free account, and you’ll be able to interact with the AI and explore its capabilities firsthand. Also, transform the way you engage with your customers and streamline your workflows with ChatGPT. It is the most powerful conversational AI platform is designed to deliver results, and now you can try it for free.

With ChatGPT, you’ll enjoy benefits like improved customer engagement, increased productivity, enhanced user experience, and faster response times… Don’t miss out on the opportunity to take your business to the next level.

Sign up for a free trial today and experience the power of ChatGPT for yourself :