swebench-test: 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)
20251027_salesforce_SAGE 44.2 44.2 29.9 1 1 NaN NaN
20250605_atlassian-rovo-dev 42 42 27.2 1 1 NaN NaN
20250522_amazon-q-developer-agent-20250405-dev 37.1 37.1 22.5 1 1 NaN NaN
20250227_sweagent-claude-3-7-20250219 33.8 33.8 20 1 0.99 NaN NaN
20250131_amazon-q-developer-agent-20241202-dev 30 30 16.8 1 0.96 NaN NaN
20241103_OpenHands-CodeAct-2.1-sonnet-20241022 29.4 29.4 16.6 1 0.95 NaN NaN
20241121_autocoderover-v2.0-claude-3-5-sonnet-20241022 24.9 24.9 13.3 1 0.9 NaN NaN
20240820_honeycomb 22.1 22.1 11.5 1 0.87 NaN NaN
20240721_amazon-q-developer-agent-20240719-dev 19.7 19.7 9.95 1 0.83 NaN NaN
20240617_factory_code_droid 19.3 19.3 9.46 1 0.82 NaN NaN
20240628_autocoderover-v20240620 18.8 18.8 9.28 1 0.82 NaN NaN
20240620_sweagent_claude3.5sonnet 18.1 18.1 9.05 1 0.8 NaN NaN
20240615_appmap-navie_gpt4o 14.6 14.6 6.67 1 0.74 NaN NaN
20240509_amazon-q-developer-agent-20240430-dev 13.8 13.8 6.57 1 0.72 NaN NaN
20240402_sweagent_gpt4 12.5 12.5 5.5 1 0.69 NaN NaN
20240728_sweagent_gpt4o 12 12 5.44 1 0.68 NaN NaN
20240402_sweagent_claude3opus 9.29 9.29 3.94 1 0.61 NaN NaN
20240402_rag_claude3opus 3.79 3.79 1.52 1 0.4 NaN NaN
20231010_rag_claude2 1.96 1.96 0.83 1 0.29 NaN NaN
20240402_rag_gpt4 1.31 1.31 0.487 1 0.24 NaN NaN
20231010_rag_swellama13b 0.697 0.697 0.254 1 0.17 NaN NaN
20231010_rag_swellama7b 0.697 0.697 0.349 1 0.17 NaN NaN
20231010_rag_gpt35 0.174 0.174 0.0614 1 0.087 NaN NaN