LLMs' reasoning process proves inefficient for creative tasks

Users are encountering inefficiency when using large language models for creative tasks that involve reasoning. The models tend to engage in extensive drafting, checking, and refining processes before producing a final output, which is seen as wasteful, especially for longer content. Attempts to control this behavior through prompting with models like Gemma 4 and Qwen 3.6 have proven difficult, suggesting it may be an inherent aspect of their reasoning methodology. AI

IMPACT Users are exploring ways to optimize LLM reasoning for creative tasks, seeking methods to reduce computational waste.

RANK_REASON User is discussing an observed behavior of LLMs, not reporting a new release or event.

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• Gemma 4
• Qwen 3.6

• other

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