  We systematically evaluated the performance of seven large language models in
generating programming code using various prompt strategies, programming
languages, and task difficulties. GPT-4 substantially outperforms other large
language models, including Gemini Ultra and Claude 2. The coding performance of
GPT-4 varies considerably with different prompt strategies. In most LeetCode
and GeeksforGeeks coding contests evaluated in this study, GPT-4 employing the
optimal prompt strategy outperforms 85 percent of human participants.
Additionally, GPT-4 demonstrates strong capabilities in translating code
between different programming languages and in learning from past errors. The
computational efficiency of the code generated by GPT-4 is comparable to that
of human programmers. These results suggest that GPT-4 has the potential to
serve as a reliable assistant in programming code generation and software
development.
