Learn/Core Concept How do recurrent depth transformers work? Recurrent depth transformers process information by repeatedly applying transformer layers at different depths, allowing models to "think longer" on complex problems. Unlike standard transformers that use fixed computation, they can dynamically decide how much processing each input needs. This architecture appears in the OpenMythos tutorial covering adaptive computation. For devs, it means models can allocate more compute to harder problems automatically, improving reasoning quality without always paying the performance cost. AdaptiveRouting |