DeepSeek
We introduce DeepSeek-Prover-V2, an open-source large language model designed for formal theorem proving in Lean 4, with initialization data collected through a recursive theorem proving pipeline powered by DeepSeek-V3.
The resulting model, DeepSeek-Prover-V2-671B, achieves state-of-the-art performance in neural theorem proving, reaching 88.9% pass ratio on the MiniF2F-test and solving 49 out of 658 problems from PutnamBench.
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35.3
Quality Score
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Arena ELO
7B
Parameters
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Context
This measures the amount of verifiable public evidence we have, not how capable the model is. A missing field means it has not been verified yet, not that its value is zero.
15 of 22 public signals
Use this section to answer one simple question first: how much outside evidence do we have that this model performs well? Structured benchmark scores appear first, then official provider evidence, then live arena signal.
This model has normalized benchmark rows, so scores here are directly comparable across benchmark sources.
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Apr 2025
Released
3/5 signals
3/4 signals
2/5 signals
3/4 signals
4/4 signals
Parameters
7B
Training compute
Not reported
Dataset scale
Not reported
Base model
DeepSeek-Prover-V1.5
Source-reported access: Open weights (restricted use) · Confident confidence
Gaps we are still tracking
These are recent benchmark or leaderboard claims from official provider sources. They are useful for freshness and context, but they are not treated the same as normalized independent benchmark rows.