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DeepSWE is a high-fidelity benchmarking platform designed to evaluate the performance of frontier AI coding agents on complex long-horizon software engineering tasks.
Unlike traditional benchmarks that reuse existing GitHub data, this system utilizes original, contamination-free tasks across five major programming languages to prevent models from relying on memorized solutions, creating a much clearer separation between frontier coding models than older public benchmarks like SWE-bench.
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