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SWE-bench: Evaluate Language Models on Open Source Software Tasks
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2025-12-05 18:23:17
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SWE-bench SWE-bench Can Language Models Resolve Real-World GitHub Issues? Paper Code Leaderboard Unassisted Assisted Model % Resolved % Date Claude 2 + BM25 Retrieval 1.96 2023-10-10 SWE-Llama 13B + BM25 Retrieval 0.70 2023-10-10 SWE-Llama 7B + BM25 Retrieval 0.70 2023-10-10 ChatGPT 3.5 + BM25 Retrieval 0.20 2023-10-10 GPT 4 + BM25 Retrieval* 0.00 2023-10-10 Model % Resolved % Date Claude 2 4.80 2023-10-10 SWE-Llama 13B 3.97 2023-10-10 SWE-Llama 7B 3.01 2023-10-10 GPT 4* 1.74 2023-10-10 ChatGPT 3.5 0.52 2023-10-10 *GPT-4 is evaluated on a random 25% subset of the dataset. The % Resolved metrics refers to the percentage of SWE-bench instances (2294 total) that were resolved by the model. For the Unassisted leaderboard, we only consider systems that have no assistance finding the relevant files in the repository. ...
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