The difference between OpenAI API and the Website Chatgpt version

ChatGPT Use cases and examples
1

Hi,

I’ve always been curious about the differences between the OpenAI API and the ChatGPT interface on the OpenAI website.

I’ve heard that there are some differences in the models used by each. For example:

  1. The API typically uses the most stable, general-purpose version of the model, while the ChatGPT website often uses a more recent model with slight fine-tuning.
  2. The API doesn’t include built-in tools like the “chain of thought” reasoning or support for uploading various file types (e.g., Word docs, Excel files). In contrast, the ChatGPT interface on the website allows users to upload a wider variety of files and has more integrated capabilities.

Question: How can we achieve similar chain-of-thought reasoning and advanced analysis features through the API, like those available in the ChatGPT interface? Are there any custom tools or components we should integrate to replicate that experience?

2

The API has a specific alias for the ChatGPT models i.e. chatgpt-4o-latest

Registered API users of reasoning models can also gain access to the thinking process for o3 and o4-mini models, with a temp of around 0.7 to 1 and function calling enabled you can allow the model to act like ChatGPT fairly effectively. It’s a lesson for the reader to implement the other niceties such as Canvas and search, etc, but that can all be done with function calling and custom code.

1 Like
3

Much appreciated your quick responses.

You mean the Chatgpt interface integrated a lot of function calling tools as default.
For example, when I upload a excel file, Chatgpt is trying to use code_interpreter generate the python code then do the analysis on the uploaded file, am I correct? And other custom code.

1 Like
4

That is correct, there is a great deal of function calling and additional custom code being executed within the ChatGPT backend.

1 Like