OpenAI Services and their Pricing

This article constitutes the second segment of a two-part series. In the initial part, we gained insights into OpenAI’s pricing structure, while in this second installment, we will comprehensively detail the pricing of each of OpenAI’s services.

In this article, we will learn about : 

• Difference between GPT-4 and GPT 3.5 Turbo
• What is Fine tune models and it’s pricing 
• What is Embedding models and it’s pricing
• What is Image Generation Model and it’s pricing 

OpenAI offers a range of API services, each with its own pricing structure. Here, we’ll provide an overview of some key OpenAI API services and their corresponding prices as of September 2023.

Language Models :

Let us begin with the prominent Language Models: GPT-4 and GPT 3.5 Turbo : 

Before we begin, let us understand about Language Models :
A language model is like a super-smart computer program that can understand and generate human-like text, making it great for writing, answering questions, and even having conversations with.

GPT 4 and GPT 3.5 Turbo express are both large language models (LLMs) that are trained on a massive dataset of text and code. They can generate text, translate languages, write different kinds of creative content, and answer your questions in an informative way. Here is a table summarizing the key differences between GPT 4 and GPT 3.5 Turbo:

Feature	GPT 4	GPT 3.5 Turbo
Parameters	175 billion	137 billion
Vocabulary	660 billion tokens	500 billion tokens
Speed	Slower	Faster
Cost	More expensive	Less expensive
Capabilities	More capable	Less capable
Optimization	General-purpose	Chat-specific

Ultimately, the best model for you will depend on your specific needs and budget. If you need a model that can generate the most accurate and coherent text, then GPT 4 is the better choice. However, if you are on a budget or need a model that is optimized for chat, then GPT 3.5 Turbo is a good option.

Know more : https://platform.openai.com/docs/models

 

Fine Tuning Models : 

Fine-tuning is like giving a machine a special course to become an expert in a specific task. Fine-tuning enhances the performance of OpenAI’s API models by offering superior results compared to traditional prompts, accommodating more training examples, and reducing token usage for shorter prompts. GPT models, pre-trained on extensive text, benefit from this approach known as “few-shot learning.” Fine-tuning further improves performance by training on an extensive dataset, reducing the need for multiple examples in prompts, thus cutting costs and lowering latency. The process entails preparing and uploading training data, training the model, and leveraging the fine-tuned model for various tasks.

Use Case : 

Fine-tuning empowers customer support chatbots by training them on company FAQs and support ticket data. This boosts their ability to offer accurate, context-aware responses, reducing manual scripting and enhancing the user experience. It leads to more effective customer service by improving the chatbot’s understanding and addressing user queries.

Model	Training (USD)	Input usage (USD)	Output usage (USD)	Pricing in INR (1 USD = 83 INR)
babbage-002	$0.0004 / 1K tokens	$0.0016 / 1K tokens	$0.0016 / 1K tokens	₹0.0332 / 1K tokens
davinci-002	$0.0060 / 1K tokens	$0.0120 / 1K tokens	$0.0120 / 1K tokens	₹0.4980 / 1K tokens
GPT-3.5 Turbo	$0.0080 / 1K tokens	$0.0120 / 1K tokens	$0.0160 / 1K tokens	₹0.6640 / 1K tokens

Know more : https://platform.openai.com/docs/guides/fine-tuning 

 

Embedding Models : 

An embedding model is like a translator for text, helping computers understand the meaning and relationships between words, which is useful for tasks like finding similar texts or organizing information.

OpenAI’s text embeddings gauge text string relatedness and find application in search ranking, clustering, recommendations, anomaly detection, diversity analysis, and text classification. Embeddings are represented as numerical vectors, with shorter distances indicating higher relatedness and longer distances implying lower relatedness between text strings.

For example, short distances indicate high text similarity, (e.g., “cat” and “dog” have smaller distances than “cat” and “car”).

Model	Usage	Pricing in USD	Pricing in INR (1 USD = 83 INR)
Ada v2	$0.0001 / 1K tokens	$0.0001 / 1K tokens	₹0.0083 / 1K tokens

Know more : https://platform.openai.com/docs/guides/embeddings/what-are-embeddings

 

Base Models : 

GPT base models, like “babbage-002” and “davinci-002,” offer natural language and code understanding and generation but lack specific instruction following training.

Example: If you were using GPT-3’s “ada” model for generating code, you can now switch to “babbage-002” as a replacement with a maximum token limit of 16,384. Similarly, for tasks previously performed with “davinci,” you can transition to “davinci-002,” both based on training data available until September 2021.

Model	Usage in USD	Pricing in INR
babbage-002	$0.0004 / 1K tokens	₹0.0332 / 1K tokens
davinci-002	$0.0020 / 1K tokens	₹0.166 / 1K tokens

Know More : https://platform.openai.com/docs/models/gpt-base

 

Image Generation : 

An image generation model is like a virtual artist that creates pictures from descriptions or edits existing images based on new ideas, helping you turn words into visuals or make creative changes to photos.

OpenAI’s Images API offers versatile image generation and manipulation capabilities. It provides capability to to generate or manipulate images with DALL·E models. It empowers users to create images from text prompts, make edits to existing images using new prompts, and generate variations of pre-existing images. OpenAI provides code samples to facilitate the exploration of these functionalities.

Example: With OpenAI’s Images API, you can turn a textual description like “a serene beach at sunset” into a beautiful image or apply creative edits to an existing image by providing a descriptive prompt. Additionally, you can generate different versions of an image, allowing for diverse artistic outputs.

Resolution	Price (USD)	Pricing in INR (1 USD = 83 INR)
1024×1024	$0.020 / image	₹1.66 / image
512×512	$0.018 / image	₹1.49 / image
256×256	$0.016 / image	₹1.32 / image

Know more : https://platform.openai.com/docs/guides/images

This article series serves as a valuable resource for readers looking to assess the capabilities and pricing of various services offered by OpenAI. From language models to image generation, it provides insights into the strengths and costs associated with each offering. Armed with this information, readers can make informed decisions about which OpenAI service best suits their specific needs and budget.