中文并非在 vibe 编码中比英语更高效：关于 token 成本和问题解决率的初步研究
Chinese Language Is Not More Efficient Than English in Vibe Coding: A Preliminary Study on Token Cost and Problem-Solving Rate
AI总结：
本文通过 SWE-bench Lite 评估中文在 LLM 编码任务中的 token 效率，发现中文并无效率优势，且成功率低于英语，提示语言切换未必带来成本节约。
摘要：
社交媒体和从业者论坛中流传着中文提示比英语在 LLM 编码任务中更 token 高效的主张，可能减少成本高达 40%。本文通过 SWE-bench Lite 评估该主张是否成立。研究发现，中文并无效率优势，token 成本因模型架构而异，且中文提示的成功率普遍低于英语。此外，成本效率以每成功任务的预期成本衡量，考虑了 token 消耗和任务解决率。这些发现为初步证据，而非结论，表明语言对 token 成本的影响模型依赖性高，从业者不应期望通过切换提示语言为中文来获得成本或性能提升。
英文摘要：
A claim has been circulating on social media and practitioner forums that Chinese prompts are more token-efficient than English for LLM coding tasks, potentially reducing costs by up to 40\%. This claim has influenced developers to consider switching to Chinese for ``vibe coding'' to save on API costs. In this paper, we conduct a rigorous empirical study using SWE-bench Lite, a benchmark of software engineering tasks, to evaluate whether this claim of Chinese token efficiency holds up to scrutiny. Our results reveal three key findings: First, the efficiency advantage of Chinese is not observed. Second, token cost varies by model architecture in ways that defy simple assumptions: while MiniMax-2.7 shows 1.28x higher token costs for Chinese, GLM-5 actually consumes fewer tokens with Chinese prompts. Third, and most importantly, we found that the success rate when prompting in Chinese is generally lower than in English across all models we tested. We also measure cost efficiency as expected cost per successful task -- jointly accounting for token consumption and task resolution rate. These findings should be interpreted as preliminary evidence rather than a definitive conclusion, given the limited number of models evaluated and the narrow set of benchmarks tested due to resource constraints; they indicate that language effects on token cost are model-dependent, and that practitioners should not expect cost savings or performance gains just by switching their prompt language to Chinese.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
