Shypd.aiThe largest open index of AI toolsDeepSeek-Prover-V2 is an open-source large language model for formal theorem proving in Lean 4. It leverages reinforcement learning for subgoal decomposition, achieving state-of-the-art performance.
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DeepSeek-Prover-V2 is an advanced open-source large language model specifically engineered for formal theorem proving within the Lean 4 environment. It employs a sophisticated recursive theorem proving pipeline, initialized with data from DeepSeek-V3, to decompose complex mathematical problems into manageable subgoals. The model then utilizes reinforcement learning to enhance its ability to bridge informal reasoning with formal proof construction. DeepSeek-Prover-V2 is available in two model sizes, 7B and 671B parameters, with the larger model built upon DeepSeek-V3-Base and the smaller on DeepSeek-Prover-V1.5-Base, featuring an extended context length of up to 32K tokens. It has demonstrated state-of-the-art performance, achieving an 88.9% pass ratio on the MiniF2F-test and solving numerous problems from PutnamBench. The project also introduces ProverBench, a benchmark dataset comprising 325 formalized problems from AIME competitions and textbook examples, designed for comprehensive evaluation across high-school and undergraduate-level mathematics.
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