一位Reddit用户正在寻找最适合生成“极小极大提示”的大型语言模型（LLM）的推荐。他们发现ChatGPT经常包含不必要的细节，导致提示过于冗长。该用户正在寻求社区的意见，了解哪些大型语言模型或方法最有效地创建简洁且有针对性的提示。 AI
排序理由 用户生成内容，寻求产品推荐，而非新闻事件。
AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →
用户寻求最适合简洁极小极大提示的大型语言模型，并指出ChatGPT冗长
本文如何被排名
- Signal score
- 0 / 100
- Composite score across the factors below. Higher = stronger signal that this story matters right now.
- Newsworthiness bucket
- Meme
- 用户生成内容，寻求产品推荐，而非新闻事件。
- Source corroboration
- Single-source cluster
- Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
- Topics
- product, opinion
- Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
- AI-industry relevance
- Standard
- On-topic for AI-industry coverage; kept in the public index.
- Story freshness
- Same-day
- Cluster formed today. Ranking reflects the current source set at time of score.
完整方法见我们的编辑标准。
报道来源 [1]
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哪种大型语言模型最适合Minimax提示？
<!-- SC_OFF --><div class="md"><p>I use ChatGPT and it works fine but I feel it just write too much extra stuff that I think is not needed. It over stuffs the prompt. In your experience which LLM or which method you've found to be best? </p> </div><!-- SC_ON -->   submitted b…