CRUXEval-input-T0.8: by models

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SE predicted by accuracy

The typical standard errors between pairs of models on this dataset as a function of the absolute accuracy.

SE vs accuracy difference

The standard error of each model pair against their observed accuracy difference. Pairs below a reference line differ by more than the corresponding number of standard errors, i.e. they are statistically distinguishable at that level.

CDF of question level accuracy

Results table by model

model pass1 pass@count win_rate count SE(A) SE_x(A) SE_pred(A)
gpt-4-0613+cot 73.7 92.2 42.8 10 1.6 1.2 1
gpt-4-0613 68 79.4 37.6 10 1.6 1.5 0.75
gpt-3.5-turbo-0613 45.7 69.4 21 10 1.8 1.4 1
phind 44.4 69.5 19.8 10 1.8 1.4 1.1
gpt-3.5-turbo-0613+cot 44.3 83.1 21.8 10 1.8 1.1 1.4
codetulu-2-34b 43.9 75.8 19.4 10 1.8 1.3 1.2
deepseek-instruct-33b 42.8 70.4 18.9 10 1.7 1.4 1.1
codellama-34b+cot 42.7 82.2 20.2 10 1.7 1.1 1.4
codellama-34b 41.1 74.9 17.7 10 1.7 1.3 1.2
magicoder-ds-7b 40.1 70.2 17.1 10 1.7 1.3 1.1
deepseek-base-33b 39.6 74.1 17.1 10 1.7 1.3 1.2
wizard-34b 38.7 63.4 16.1 10 1.7 1.4 1
codellama-python-34b 37 66.6 15.1 10 1.7 1.3 1.1
deepseek-base-6.7b 36.9 70.5 15.5 10 1.7 1.2 1.2
codellama-13b+cot 36.4 78.2 16.4 10 1.7 1 1.4
codellama-13b 35.2 71 14.3 10 1.7 1.2 1.2
deepseek-instruct-6.7b 34.7 59.5 14 10 1.7 1.3 1
mixtral-8x7b 32.8 68.9 13.2 10 1.7 1.2 1.2
codellama-python-13b 32.5 65.6 12.8 10 1.7 1.2 1.2
wizard-13b 32.2 58.6 12.5 10 1.7 1.3 1
codellama-python-7b 31.6 66.4 12.6 10 1.6 1.1 1.2
codellama-7b+cot 30 73.4 12.9 10 1.6 0.92 1.3
codellama-7b 28.4 63.1 10.6 10 1.6 1.1 1.1
mistral-7b 27.6 62.4 10.3 10 1.6 1.1 1.1
starcoderbase-16b 25.8 59.1 9.51 10 1.5 1.1 1.1
phi-2 25.7 60.8 10.4 10 1.5 1 1.1
starcoderbase-7b 25.4 56.1 9.18 10 1.5 1.1 1.1
deepseek-instruct-1.3b 24 46.6 9.07 10 1.5 1.2 0.92
deepseek-base-1.3b 22.5 54.1 8.25 10 1.5 1 1.1
phi-1.5 16.1 47.8 6.37 10 1.3 0.8 1
phi-1 12.6 25.4 4.03 10 1.2 0.96 0.67