https://huggingface.co/spaces/lmsys/chatbot-arena-leaderboar...
https://huggingface.co/spaces/lmsys/chatbot-arena-leaderboar...
I was feeding multiple python and c# coding challenges / questions to both and Opus blew GPT4 out of the water on every single task. Didn’t matter if I was giving them 50 lines or 5,000 Opus would consistently give working/correct solutions while GPT4 preferred to answer with pseudo code, half complete code with ‘do the thing here’ comments, or would just tell me that it’s too complicated.
I have them working with mostly C++ and Clojure, a bit of Python, and Vimscript every once in a while. Both models are much better at Python and fairly bad at Vimscript. Clojure failure cases are mostly from invented functions and being bad at modifying existing code. I can't pick out a strong pattern in how they fail with C++, but there have been a few times where GPT4 ends up looping between the same couple unworkable solutions (maybe this indicates a poor understanding of prior context?).
I mostly use it to make react/javascript front ends to a python/fastapi backend and chatGPT4 is great at that.
I tried to write a piece of music though in the old Csound programming language and it barely even works.
It will be interesting to see how the context plays out because I have noticed that I can often give it extra context that I think will be helpful but end up causing it to go down a wrong path. I might even say my best results have been from the most precise instructions inside the smallest possible context.
I guess you benchmarked via API? I've heard even the datestamped models have been nerfed from time to time..