📄 中文摘要
研究提出了一种新的方法，通过优化Claude模型的输出，成功将输出令牌数量减少了63%。这一技术改进不仅提升了模型的效率，还降低了计算成本，使得在处理大规模文本时更加高效。通过对模型架构和输出机制的深入分析，研究者们发现了多种可以减少冗余信息的策略，从而在保持输出质量的同时，显著提高了处理速度。这一进展为自然语言处理领域的应用提供了新的可能性，尤其是在资源有限的情况下，能够更好地满足用户需求。
Universal Claude.md – 将Claude输出令牌减少63%
出处: Universal Claude.md – cut Claude output tokens by 63%
发布: 2026年3月31日
📄 English Summary
Universal Claude.md – cut Claude output tokens by 63%
A new method has been proposed that successfully reduces the output tokens of the Claude model by 63% through optimization techniques. This improvement enhances the model's efficiency and lowers computational costs, making it more effective for processing large-scale texts. By conducting an in-depth analysis of the model architecture and output mechanisms, researchers identified various strategies to minimize redundant information, thereby significantly increasing processing speed while maintaining output quality. This advancement opens up new possibilities for applications in the field of natural language processing, particularly in scenarios with limited resources, better meeting user demands.