This article introduces Mixture-of-Recursions (MoR), a framework that enhances the efficiency of language models by combining parameter sharing and adaptive computation. MoR dynamically adjusts recursion depths for individual tokens, improving memory access and reducing computational costs while maintaining model performance. It shows significant improvements in validation perplexity and few-shot accuracy across various model sizes.