[badFEengineer]

nice, I've been looking for something like this! A few notes / wishlist items:

* Looks like for gpt-4 turbo (https://artificialanalysis.ai/models/gpt-4-turbo-1106-previe...), there was a huge latency spike on December 28, which is causing the avg. latency to be very high. Perhaps dropping top and bottom 10% of requests will help with avg (or switch over to median + include variance)

* Adding latency variance would be truly awesome, I've run into issues with some LLM API providers where they've had incredibly high variance, but I haven't seen concrete data across providers

[Gcam]

Thanks for the feedback and glad it is useful! Yes, agree might better representative of future use. I think a view of variance would be a good idea, currently just shown in over-time views - maybe a histogram of response times or a box and whisker. We have a newsletter subscribe form on the website or twitter (https://twitter.com/ArtificialAnlys) if you want to follow future updates

[AaronFriel]

Variance would be good, and I've also seen significant variance on "cold" request patterns, which may correspond to resources scaling up on the backend of providers.

Would be interesting to see request latency and throughput when API calls occur cold (first data point), and once per hour, minute, and per second with the first N samples dropped.

Also, at least with Azure OpenAI, the AI safety features (filtering & annotations) make a significant difference in time to first token.