MTG Bench: Testing how well LLMs can play Magic
A developer discusses the challenges of using Large Language Models to play Magic: The Gathering without a formal rules engine. The post explores the technical limitations of LLM agent loops and the cost inefficiencies of current token caching models.
Why it matters
It provides insight into the practical limitations of LLMs in complex, rule-based environments and highlights developer frustrations with current AI API pricing structures.
Click on the charts above to view each benchmark's simulations.
The content is a technical discussion regarding software development and AI architecture with no political or social bias.
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