new5월 27일· 1 sources
The LLM Efficiency Paradox: Why Better Prompts Often Lead to Bloated Code
"효율적으로 짜줘"의 역설, LLM 10종 코드 최적화 성능 분석
Why it matters
A benchmarking study of 10 major LLMs shows that explicit efficiency prompts only benefited GPT-5.4, while others either ignored them or produced worse results. These findings suggest that for most models, natural output tendencies are more reliable than manual optimization instructions in production environments.
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GPT-5.4Gemma 4 31Bcode efficiencyprompt engineeringLLM benchmarkstoken optimization