Evaluating a new model on existing responses

In the following eval, we are going to compare how a new model (gpt-4.1-mini) compares to our old model (gpt-4o-mini) by evaluating it on some stored responses. The benefit of this is for most developers, they won't have to spend any time putting together a whole eval -- all of their data will already be stored in their logs page.

We want to see how gpt-4.1 compares to gpt-4o on explaining a code base. Since can only use the responses datasource if you already have user traffic, we're going to generate some example traffic using 4o, and then compare how it does to gpt-4.1.

We're going to get some example code files from the OpenAI SDK, and ask gpt-4o to explain them to us.

Now, lets generate some responses.

Note that in order for this to work, you'll have to be doing this on an org where data logging isn't disabled (through zdr, etc). If you aren't sure if this is the case for you, go to https://platform.openai.com/logs?api=responses and see if you can see the responses you just generated.

First, lets kick off a run to evaluate how good the original responses were. To do this, we just set the filters for what responses we want to evaluate on

Now, let's see how 4.1-mini does!

Now, lets go to the dashboard to see how we did!