Differences between GPT-3.5 and GPT-4

This article compares the differences between OpenAI's GPT-3.5 and GPT-4 AI language models.


The GPT-3.5 models are characterized by their ability to understand and generate both natural language and code. The model series offers different variants tailored to different usage scenarios.

The most prominent model of the GPT-3.5 series is GPT-3.5-Turbo. Not only is it the most powerful model in the GPT-3.5 family, but it has also been optimized specifically for chat. It can also be used efficiently for traditional text completion tasks. GPT-3.5 models can process up to 4,096 tokens and have been trained with data up to September 2021.


GPT-4 is the latest and most advanced model from OpenAI. It builds on the capabilities of the previous models and adds significant improvements, especially in terms of handling complex reasoning tasks. It can handle up to 8,192 tokens and offers improved creativity and cooperation over previous models. GPT-4 is even better at generating, editing, and iterating creative and technical writing tasks together with users.

In addition, GPT-4 has been improved with feedback from ChatGPT users and over 50 experts in areas such as AI security and safety. This process has helped make GPT-4 more secure and useful, and equipped it with broader general knowledge and improved problem-solving capabilities.

Main differences

For many basic tasks, the difference between GPT-4 and GPT-3.5 models is not significant. The biggest differences between GPT-3.5 and GPT-4 are in their performance and application capabilities. While GPT-3.5 already offers remarkable performance in natural language and code processing, GPT-4 surpasses this model with improved reasoning and problem-solving capabilities.

GPT-4 can handle up to 8,192 tokens, twice as many as GPT-3.5, making it better for longer and more complex tasks. In addition, by incorporating user and expert feedback into its development, GPT-4 is better able to provide more secure and useful responses.

GPT-4 also demonstrates improved handling of context and text comprehension. It can better understand the context of a conversation or text input, generating more relevant and nuanced responses. This capability may prove particularly useful in applications that require a deeper understanding of context, such as customer service chats, where understanding customer queries and generating appropriate responses is critical.

In conclusion, GPT-4 can be seen as a continuation of the continuous improvement and adaptation of AI systems to the needs of users and society. With each new version, models like GPT-4 bring us closer to the vision of artificial intelligence capable of handling complex tasks and delivering real value in a wide range of use cases.

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