swebench-bash-only: 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)
Claude 4.5 Opus medium (20251101) 74.4 74.4 24 1 2 NaN NaN
Gemini 3 Pro Preview (2025-11-18) 74.2 74.2 23.8 1 2 NaN NaN
GPT-5.2 (2025-12-11) (high reasoning) 71.8 71.8 22.6 1 2 NaN NaN
Claude 4.5 Sonnet (20250929) 70.6 70.6 21.6 1 2 NaN NaN
GPT-5.2 (2025-12-11) 69 69 21.3 1 2.1 NaN NaN
Claude 4 Opus (20250514) 67.6 67.6 19.2 1 2.1 NaN NaN
GPT-5.1 (2025-11-13) (medium reasoning) 66 66 18.8 1 2.1 NaN NaN
GPT-5.1-codex (medium reasoning) 66 66 18.5 1 2.1 NaN NaN
GPT-5 (2025-08-07) (medium reasoning) 65 65 17.9 1 2.1 NaN NaN
Claude 4 Sonnet (20250514) 64.8 64.8 17.8 1 2.1 NaN NaN
Kimi K2 Thinking 63.4 63.4 17.3 1 2.2 NaN NaN
Minimax M2 61 61 16.8 1 2.2 NaN NaN
DeepSeek V3.2 Reasoner 60 60 16.8 1 2.2 NaN NaN
GPT-5 mini (2025-08-07) (medium reasoning) 59.8 59.8 15.4 1 2.2 NaN NaN
o3 (2025-04-16) 58.4 58.4 15.2 1 2.2 NaN NaN
Devstral small (2512) 56.4 56.4 14.9 1 2.2 NaN NaN
Qwen3-Coder 480B/A35B Instruct 55.4 55.4 14.3 1 2.2 NaN NaN
GLM-4.6 (T=1) 55.4 55.4 13.8 1 2.2 NaN NaN
GLM-4.5 (2025-08-22) 54.2 54.2 13 1 2.2 NaN NaN
Devstral (2512) 53.8 53.8 14.2 1 2.2 NaN NaN
Gemini 2.5 Pro (2025-05-06) 53.6 53.6 13 1 2.2 NaN NaN
o4-mini (2025-04-16) 45 45 9.96 1 2.2 NaN NaN
Kimi K2 Instruct 43.8 43.8 10.3 1 2.2 NaN NaN
GPT-5 nano (2025-08-07) (medium reasoning) 34.8 34.8 7.36 1 2.1 NaN NaN
gpt-oss-120b 26 26 5.24 1 2 NaN NaN
Llama 4 Maverick Instruct 21 21 3.91 1 1.8 NaN NaN
Claude 3.7 Sonnet (20250219) 10.2 10.2 2.13 1 1.4 NaN NaN
Qwen2.5-Coder 32B Instruct 9 9 1.27 1 1.3 NaN NaN