DeepSeekMath-V2 is a state-of-the-art mathematical reasoning model built on the DeepSeek-V3.2-Exp-Base architecture with 685 billion parameters. Unlike conventional math-focused language models that optimize only for correct final answers, DeepSeekMath-V2 introduces a self-verification framework where the model generates, inspects, and validates its own mathematical proofs.

This approach enables rigorous, step-by-step reasoning suitable for theorem proving, scientific research, and domains requiring high-integrity logic. The model is trained through a generation-verification loop involving a dedicated LLM-based verifier and reinforcement learning optimized for proof correctness rather than answer matching.

DeepSeekMath-V2 achieves gold-level scores on IMO 2025 and CMO 2024, along with a groundbreaking 118/120 on the Putnam 2024 contest. Released under the Apache 2.0 license and hosted on Hugging Face, it is fully open source for research and commercial use.

DeepSeekMath-V2 Launches with 685B Parameters - Dominates Math Contests