DeepSeek-Math-V2

What is DeepSeek-Math-V2?

DeepSeek-Math-V2 is the world's first open-source International Mathematical Olympiad (IMO) gold medal level by the DeepSeek team.mathematical reasoningLarge ModelDeveloped based on the DeepSeek-V3.2 experimental architecture, it adopts the Apache 2.0 license with full open-source rights. Its core breakthrough lies inSelf-validating mathematical reasoning--Through the closed-loop architecture of “Generate-Verify-Optimize”, the model achieves a qualitative leap from merely pursuing the correctness of answers to a rigorous reasoning process. In the 2025 IMO simulation competition, the model won the gold medal with a correct rate of 83.3% (5/6 questions); in Putnam 2024, which is known as “the world's toughest math competition for college students”, the model even achieved a nearly perfect score of 118/120, far exceeding the highest score of 90 in human history. The highest score in history was 90 points, demonstrating the ultimate mastery of complex logical derivations.

DeepSeek-Math-V2's core technology

• Dual System Closed Loop Architecture: A generator and a validator are used for co-design. The generator is responsible for producing solution steps, while the validator reviews the logical rigor, formula accuracy and derivation completeness line by line, and drives continuous optimization of the generator through a feedback mechanism. For example, in theorem proving, the verifier can automatically identify logical loopholes and trigger corrections, forming a self-iterative reasoning enhancement loop.
• Self-validation training frameworkThe core optimization goal of AI is to break through the limitation of traditional AI of “focusing on the answer but not on the process”, and make the reliability of the reasoning chain the core optimization goal. By expanding the verification computing resources to automatically annotate difficult samples and continuously improving the performance of the verifier, we ensure that even in the face of open-ended problems without clear answers (such as theorem proving), we can still output a logically flawless derivation process.
• Open Source Ecological EmpowermentThe model weights and code are synchronized and open-sourced to Hugging Face and GitHub, promoting the proliferation of “self-verification” technology to code, law and other fields, forming a universal intelligent base. According to the estimation of scientific research institutions, this technology can shorten the breakthrough cycle of mathematical theories by 30%, and reduce the cost of manual auditing to 1/5 in “zero-defect” scenarios such as financial derivatives pricing.

Scenarios for the use of DeepSeek-Math-V2

• Mathematics competitions and research assistance: Reaching gold medal level in IMO, CMO, Putnam and other top tournaments, the model can automatically complete the derivation and verification of complex theorems, freeing researchers from tedious calibration. For example, in topology research, the model can quickly verify the rigor of conjecture derivation and accelerate theoretical breakthroughs.
• Education Intelligence Upgrade: As a core tool for personalized tutoring, it diagnoses students' proof loopholes in real time. Head educational institutions real test shows that the VIP renewal rate can be increased by 8%-12%.Combined with Kimi and other tools, it can generate the interdisciplinary teaching design PPT of "The Records of the Yueyang Tower" in 10 minutes, supporting online editing and format export.
• Industrial-scale applications on the groundIn the financial field, it can accurately price complex derivatives; in aviation software validation, it ensures zero defects in code logic; in daily development, it supports code completion, test script generation, and technical documentation writing, improving development efficiency by more than 351 TP4T.

Project address and open source protocol

• GitHub repository::https://github.com/deepseek-ai/DeepSeek-Math-V2
• HuggingFace Model Library::https://huggingface.co/deepseek-ai/DeepSeek-Math-V2
• Technical Papers::https://github.com/deepseek-ai/DeepSeek-Math-V2/blob/main/DeepSeekMath_V2.pdf

Why DeepSeek-Math-V2?

1. Technology Benchmarking: The world's first open source IMO gold model, defining a new standard for AI mathematical reasoning.
2. Reliability Revolution: The self-validation mechanism reduces the inference error rate to 0.7%, which far exceeds that of similar models.
3. Ecological openness: Provides a choice of parameter sizes from 7B to 685B and supports local deployment and cloud invocation.
4. Cross-cutting potential: Verification frameworks can be migrated to code, law, and other domains to build generalized self-verifying AI pedestals.