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Can a MUD evaluate LLMs? A $99 proof of concept
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Overview
CrucibleBench places language models in a persistent MUD environment where NPCs can remember interactions, accumulate trust, and leave traces of mistakes. The system evaluates AI performance over 50 turns with hidden social objectives, utilizing established technology in innovative ways.
Summary from cruciblebench.ai.
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cruciblebench.ai
Can a MUD evaluate LLMs? A $99 proof of concept
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Community reactions
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Hacker News · cruciblebench.ai
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Historical count: 5 · 5 saved in sample · Historical sample
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Based on 5 sampled comments from this thread. Analyzed 2026-07-23.
- Praise: Integrating LLMs with MUDs could spark a revival of text-based gaming, making it more engaging for a new generation.
- Praise: One commenter is having a blast letting agents interact in a MUD, showcasing the potential for LLMs to autonomously build maps and classify events.
- Praise: The idea of using a MUD as a testing ground for LLMs is brilliant; it leverages text as the native environment for these models.
- Concern: There's a sense of frustration about the decline of MUDs, with some blaming Discord for its shortcomings, but others argue it's more about user engagement.
- Concern: The skepticism about whether MUDs can truly compete with modern social platforms highlights a concern about their relevance.