GPT-4 vs GPT-3: What are the differences between these models?

OpenAI announced the GPT-4 model on March 14, 2023. GPT-4 is the most advanced and recent model announced by OpenAI so far. Here, we will thoroughly compare the GPT-4 vs GPT-3 model and highlight the differences.

GPT-4 vs GPT-3 Comparison In Summary

  • GPT-3 was released on June 11, 2020, while GPT-4 was released on March 14, 2023. Before GPT-3, there were the GPT-2 model, released in 2019, and the GPT-1 model, released in 2018.
  • GPT stands for Generative Pre-trained Transformer, which is a type of machine learning artificial intelligence product capable of performing natural language processing tasks.
  • GPT-3 was trained with 175 billion parameters. Although the exact number of parameters for GPT-4 has not been disclosed by OpenAI, it is speculated to be at least 10 times larger than that of GPT-3.
  • GPT-4 is more reliable, creative, and able to handle much more nuanced instructions than GPT-3.
  • GPT-3 was further enhanced and evolved into GPT-3.5, which served as the foundation for the creation of ChatGPT. On the other hand, after its release, GPT-4 was integrated into ChatGPT, allowing it to be utilized by ChatGPT Plus members.
  • GPT-4 has the ability to be multimodal, which means it can accept not only text inputs but also image inputs. This sets it apart from GPT-3, which only accepts text inputs.
  • GPT-4 exhibits a higher reasoning ability. Additionally, GPT-4 demonstrates enhanced creativity compared to GPT-3. GPT-4 also outperforms GPT-3 in complex inquiries and queries.
  • GPT-4, despite its high reasoning ability and creativity, has a response time that is 1.7 times slower compared to GPT-3.
  • Both GPT-4 and GPT-3 models have a character limit. The standard GPT-4 model provides a context length of 8k tokens. OpenAI also offers an extended model with a context length of 32k tokens. In comparison, the context length for the GPT-3 model is 4k and 16k tokens.
  • The usage cost for the standard GPT-3 API is $0.0015 per 1K tokens for 4K context and $0.003 per 1K tokens for 16K context. In contrast, the standard GPT-4 API has a usage cost of $0.03 per 1K tokens for 8K context and $0.06 per 1K tokens for 32K context. For more information, visit OpenAI’s pricing page.

GPT-4 and GPT-3: Comparison of Usage

You can access and use both the GPT-4 and GPT-3 models from OpenAI by obtaining API tokens and having basic coding knowledge. Check out our post to learn in detail how to call the GPT-4 API.

To call the GPT-4 API in Node.js in a simplified manner, you need to execute the following function:

const completion = await openai.createChatCompletion({
  model: "gpt-4",
  messages: [{role: "user", content: "Hello world"}],

To call the GPT-3 API, you can modify the function call as follows:

const completion = await openai.createChatCompletion({
  model: "gpt-3.5-turbo",
  messages: [{role: "user", content: "Who won the world series in 2020?"}],

Additionally, you can access both models, GPT-4 and GPT-3, through ChatGPT with certain limitations, without making direct API calls. Learn how to access GPT-4 model in ChatGPT.

GPT-4 and GPT-3: Comparison of Pricing

The usage cost of the GPT-4 model is approximately 20 to 30 times more expensive compared to GPT-3.

The pricing for GPT-4 and GPT-3 models, per token, is as follows:


  • 8K context: $0.03 per 1K tokens for input, $0.06 per 1K tokens for output
  • 32K context: $0.06 per 1K tokens for input, $0.12 per 1K tokens for output


  • 4K context: $0.0015 per 1K tokens for input, $0.002 per 1K tokens for output
  • 16K context: $0.003 per 1K tokens for input, $0.004 per 1K tokens for output

GPT-4 and GPT-3: Comparison of Capabilities

GPT-4 outperforms GPT-3 in tasks such as text completion, translation, and summarization due to its larger number of parameters, making it the most advanced and up-to-date model. It demonstrates superior language generation capabilities.

Additionally, GPT-4 performs better in languages, particularly languages other than English, compared to GPT-3. It demonstrates higher reasoning ability and creativity.

GPT-4 is more successful in understanding and answering complex queries. However, its only drawback is that it has slower response times compared to GPT-3.

According to OpenAI document, GPT-3 only achieved a score in the 10th percentile on the bar exam, whereas GPT-4 scored in the 90th percentile, with a score of 298 out of 400.

GPT-4 excelled in the SAT Reading & Writing section, achieving a score of 710 out of 800 according to the same document. This places it in the 93rd percentile among test-takers. On the other hand, GPT-3.5 scored in the 87th percentile with a score of 670 out of 800.

Also Read: GPT-4 Exam Scores

GPT-4 is more creative, and able to handle much more nuanced instructions than GPT-3.

GPT-4 and GPT-3: Comparison of Accuracy in Responses

Hallucination in a language model refers to the generation of responses that are nonsensical or unrelated to the input.

GPT-3 model has a chance of approximately 15% to 20% for hallucination. However, in the case of the GPT-4 model, this percentage is 40% lower. The CEO of OpenAI, Sam Altman, has stated that GPT-4 hallucinates significantly less and is less biased compared to its predecessor.

Overall, GPT-4 is more reliable in responses compared to GPT-3 model.

Learn More: How reliable is ChatGPT in giving responses

GPT-4 vs GPT-3: Image Interpretation

GPT-4, unlike its predecessors, possesses the capability of being multimodal. This means it can accept images as input and comprehend what is depicted in those images. It can even fulfill requests based on a sketch drawn on paper, such as developing a mobile application.

In the article where OpenAI introduced the GPT-4 model, they shared the following image, indicating that GPT-4 is capable of understanding and providing commentary on the peculiarity depicted in the image.

gpt-4 can understand image

The GPT-3 model don’t have the ability to read images. They are only capable of accepting text input and generating text-based responses.

Also Read: GPT-4 Image Input GPT-4 Vision

GPT-4 vs GPT-3: Character Limits

Tokens are the fundamental units of text for GPT models. These models have a limit on the number of tokens they can process and generate. A general rule of thumb is that 4 token corresponds to approximately 3 characters in common English text.

The GPT-4 model has two variants with different token limits: an 8,192 token model and a 32,768 token model. For the 8K model, there is a character limit of 8,192 token or approximately 6,144 English characters, while the 32K model has a character limit of 24.576, equivalent to almost 50 pages of text.

For GPT-3, there are two variants with 4K and 16K context, which correspond to character limits of approximately 3,000 and 12,000 English characters, respectively.

In comparison, the token limit of the GPT-4 model is 2 to 8 times higher than that of GPT-3, depending on the specific variant.

GPT-4 vs GPT-3: Bottom Line

GPT-4, released approximately three years after GPT-3, represents OpenAI’s most advanced and up-to-date language model.

With around 10 times more parameters than GPT-3, it exhibits greater reasoning abilities, enhanced creativity, and the ability to process image inputs.

Additionally, GPT-4 provides less biased responses. The drawbacks of GPT-4 are slightly slower response times and higher usage costs.

Learn More: All OpenAI’s GPT Models

In the comparison between GPT-4 and GPT-3, the former emerges as the clear winner—it is larger, more intelligent, and more creative than its predecessor.