[Usage]: How different between 'obtain the full response' and 'fixed length output' when using benchmark performance test

[ZombieBlue]

Your current environment

I noticed that the official way of using the benchmark to call the chat API doesn't involve continuous concurrency and doesn't obtain the full response. However, I use Locust to continuously and concurrently call the chat API and obtain the full output.

1、When these two methods are used to evaluate the performance of the model and the accelerator card, what are the differences?

2、The benchmark script also provides a test method with fixed - length input and output. What are the differences in calculating the token output rate between this method and the test method of asking random questions and obtaining a full response?

How would you like to use vllm

I want to run inference of a [specific model](put link here). I don't know how to integrate it with vllm.

Before submitting a new issue...

• Make sure you already searched for relevant issues, and asked the chatbot living at the bottom right corner of the documentation page, which can answer lots of frequently asked questions.

[github-actions]

This issue has been automatically marked as stale because it has not had any activity within 90 days. It will be automatically closed if no further activity occurs within 30 days. Leave a comment if you feel this issue should remain open. Thank you!

[github-actions]

This issue has been automatically closed due to inactivity. Please feel free to reopen if you feel it is still relevant. Thank you!