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While autoregressive decoder models dominate the Large Language Model (LLM) arena, Diffusion-Encoder LLMs offer potential benefits like reduced hallucination and improved efficiency. A recent online discussion investigates the reasons behind their comparatively limited adoption. The analysis examines the inherent trade-offs between these two approaches, scrutinizing the computational demands and questioning the prevailing reliance on softmax attention. The debate also identifies promising areas for future research aimed at unlocking the full potential of Diffusion-Encoder LLMs. The original discussion is available on Reddit: https://old.reddit.com/r/artificial/comments/1mmemn9/why_are_diffusionencoder_llms_not_more_popular/.