LLMadness – March Madness Model Evals

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I wanted to play around with the non-coding agentic capabilities of the top LLMs so I built a model eval predicting the March Madness bracket.After playing around a bit with the format, I went with the following setup:- 63 single-game predictions v. full one-shot bracket- Maxed out at 10 tool calls per game- Upset-specific instruction in the system prompt- Exponential scoring by round (1, 2, 4, 8, 16, 32)There were some interesting learnings:- Unsurprisingly, most brackets are close to chalk. Very few significant upsets were predicted.- There was a HUGE cost and token disparity with the exact same setup and constraints. Both Claude models spent over $40 to fill in the bracket while MiMo-V2-F

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Website: llmadness.com/2026