swebench-test: by models

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p-values for model pairs

The null hypothesis is that model A and B each have a 1/2 chance to win whenever they are different, ties are ignored. The p-value is the chance under the null-hypothesis to get a difference as extreme as the one observed. For all pairs of models, this mainly depends on the difference in accuracy. Hover over each model pair for detailed information.

p-values vs. differences

The range of possible p-values vs. the difference in accuracy over all pairs.

Differences vs inconsistencies

Here is a more informative figure of the source information used to compute p-value. Any model pair to the right of the parabola is statistically different from each other at the given level. This plot shows a pretty sharp transition since there are no model pairs with a small #A_win + #B_win, which rules out significant results at a small difference in |#A_win-#B_win|. For more explanation see doc.

Results table by model

We show 3 methods currently used for evaluating code models, raw accuracy used by benchmarks, average win-rate over all other models (used by BigCode), and Elo (Bradly-Terry coefficients following Chatbot Arena). Average win-rate always have good correlation with Elo. GPT-3.5 gets an ELO of 1000 when available, otherwise the average is 1000.

model pass1 win_rate elo
20240820_honeycomb 22.1% 84.5% 1392.5
20240721_amazon-q-developer-agent-20240719-dev 19.7% 80.3% 1345.7
20240617_factory_code_droid 19.3% 79.7% 1336.4
20240628_autocoderover-v20240620 18.8% 78.2% 1323.2
20240620_sweagent_claude3.5sonnet 18.1% 75.6% 1302.0
20240615_appmap-navie_gpt4o 14.6% 66.1% 1215.7
20240509_amazon-q-developer-agent-20240430-dev 13.8% 62.7% 1197.8
20240402_sweagent_gpt4 12.5% 58.1% 1158.6
20240728_sweagent_gpt4o 12.0% 55.9% 1145.6
20240402_sweagent_claude3opus 9.3% 44.3% 1060.8
20240402_rag_claude3opus 3.8% 17.6% 845.9
20231010_rag_claude2 2.0% 9.3% 724.1
20240402_rag_gpt4 1.3% 5.7% 622.4
20231010_rag_swellama13b 0.7% 3.1% 520.9
20231010_rag_swellama7b 0.7% 3.8% 562.8
20231010_rag_gpt35 0.2% 0.7% 245.7