A new leaderboard tests if chain-of-thought actually helps your model
Hugging Face just launched the Open CoT Leaderboard to measure how much chain-of-thought prompting actually boosts LLM accuracy, rather than tracking absolute benchmark scores. Early results from 30 models reveal small 7B models often gain more from step-by-step reasoning than giants, though CoT can occasionally backfire and degrade accuracy. It gives developers a real look at prompt effectiveness beyond raw capability.