Introducing PerfGPT – analyze your performance test results using OpenAI

In the past couple of posts we have discussed how to use ChatGPT for JMeter tasks and use cases for performance engineers. In this blog post, I am happy to introduce PerfGPT an open source tool to analyze your performance test results using the OpenAI model.

What is PerfGPT?

PerfGPT is an open source web application which helps in analyzing performance test results using the OpenAI model. It is completely free to use, even for commercial purposes.

About PerfGPT

PerfGPT backbone is OpenAI API. PerfGPT is a lightweight web application which is built using Flask – a Python framework for web development.

How to use PerfGPT?

Head to to login using GitHub account.

PerfGPT Login
PerfGPT Login

PerfGPT requires only minimal info from your GitHub account. It will not read nor make any changes to your repos. After successful login, click Upload button which will take you to the upload page.

You can upload your test results either in JSON, CSV, or JTL. The recommended upload format is CSV. Select the file and then click on the Upload button.

Upload to PerfGPT
Upload to PerfGPT

Upon clicking the Upload button, PerfGPT will process the data and present its findings as shown below.

PerfGPT Results
PerfGPT Results

PerfGPT generates two summaries: High level and Detailed summary. This analysis will help performance engineers to draw the conclusion from the raw performance test results without spending more time on manual analysis using spreadsheet programs or analytics tools.


  • Free and Open Source
  • No need to use your OpenAI API key
  • PerfGPT will not read or store your raw test data.
  • Fast OpenAI analysis for your raw performance results
  • Tool agnostic analysis. You can upload the results from any performance testing tools.
  • Slack integration


  • 10 MiB file upload size limit
  • 10 uploads per month
  • Results accuracy still needs improvement. Eventually the OpenAI model will be good at it.


PerfGPT is a web application that is both free and open source. It assists performance engineers in efficiently analyzing raw data through the use of an OpenAI model, allowing them to focus on their other responsibilities. Additionally, the OpenAI model will continue to enhance its precision in processing raw data in the near future.

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