Chinese AI lab DeepSeek has released DeepSeek-Prover-V2-671B, an exceptionally large language model aimed at mathematical theorem proving, making it available on Hugging Face. The release continues the company’s pattern of open-sourcing powerful models even as it navigates intense geopolitical scrutiny, particularly from the United States, and adapts to tightening US export controls on advanced computing hardware that have been in place since late 2022.
DeepSeek-Prover-V2-671B appears ahead of the soon expected release of its next reasoning model DeepSeek R2, which the company is pushing for an earlier-than-planned rollout as it battles tightening U.S. and European regulations and intensifying competition from OpenAI, Google, Anthropic, xAI, and Alibaba.
Efficiency Under Constraints
These hardware restrictions, limiting access to top-tier Nvidia GPUs like the A100 and H100, appear to have driven DeepSeek’s focus on computational efficiency. The company incorporated techniques like Multi-Head Latent Attention (MLA)—an approach designed for efficiently handling long data sequences (up to 128,000 tokens in its V3 base model)—and FP8 quantization, a low-precision numerical format that reduces memory needs, into its model architecture.
This efficiency focus was previously highlighted when DeepSeek open-sourced infrastructure tools like the FlashMLA attention kernel and the 3FS distributed file system in April 2024. DeepSeek-V3, the likely foundation for Prover V2, was trained on a substantial cluster of 2048 Nvidia H800 GPUs, according to its technical report.
AI Tackles Formal Mathematics
DeepSeek-Prover-V2-671B isn’t a general chatbot but a highly specialized system targeting formal theorem proving, specifically using the Lean 4 proof assistant language. Lean 4 is an interactive tool used to formalize mathematical definitions and proofs and check their correctness computationally.
It is a powerful proof assistant and programming language that provides the framework for expressing mathematical arguments formally and computationally verifying their correctness. DeepSeek-Prover-V2 interacts with this framework, likely generating or suggesting proof steps in Lean 4 syntax, which are then checked by the Lean 4 environment itself to ensure logical soundness. This synergy aims to make the complex task of formal verification more manageable.
The model uses a massive 671 billion total parameters, distributed in the secure safetensors format. However, its Mixture-of-Experts (MoE) architecture—a design routing input to only a subset of parameters—means only a fraction are active during inference, balancing scale with computational cost.
Potential applications include automatically generating step-by-step proofs, detecting errors in existing proofs, aiding teaching, and assisting researchers. This builds on DeepSeek’s prior work, including the 7B parameter DeepSeek-Prover-V1.5 (detailed August 2024), which used techniques like Reinforcement Learning from Proof Assistant Feedback (RLPAF) for Lean 4, itself an evolution from their initial Prover work (May 2024).
This approach differs from other recent high-profile math AI systems. Google DeepMind’s AlphaGeometry2, which recently surpassed human gold medalists on International Mathematical Olympiad (IMO) geometry problems, employs a hybrid architecture combining a fine-tuned Gemini language model with a dedicated symbolic reasoning engine (DDAR).
AlphaGeometry2 also relied heavily on generating vast amounts of synthetic training data (over 300 million theorems and proofs) to achieve its performance on competition-style geometry problems. DeepSeek’s earlier Prover models (V1.5 and V1) also utilized synthetic data generation and techniques like Reinforcement Learning from Proof Assistant Feedback (RLPAF) and Monte Carlo Tree Search (MCTS) variants, suggesting Prover V2 likely builds on similar methods, albeit scaled up significantly for its 671B size.
Meanwhile, Microsoft’s rStar-Math framework takes a contrasting path, focusing on enhancing the mathematical reasoning capabilities of small language models (SLMs). It uses techniques like MCTS, code-augmented Chain-of-Thought (CoT) reasoning (producing both natural language and verifiable Python code), and a Process Preference Model (PPM) to evaluate intermediate steps, enabling 7-billion parameter models to achieve high accuracy on benchmarks like GSM8K and MATH.
While DeepSeek pushes the boundaries of scale for formal proof generation within Lean 4, AlphaGeometry targets Olympiad geometry with a hybrid symbolic/neural approach, and rStar-Math optimizes smaller models for broader math reasoning tasks.
Potential applications for DeepSeek-Prover-V2 include automatically generating step-by-step proofs, detecting errors in existing proofs, aiding teaching, and assisting researchers in exploring new theorems within the Lean 4 ecosystem.
Caught In Geopolitical Crosshairs
The release occurs as DeepSeek faces intense regulatory action. In early 2025, the US Navy prohibited its use over security risks, followed shortly by Texas banning the chatbot app on state government devices.
Discussions about potential broader US government restrictions also surfaced around this time. This pressure was significantly amplified by an April 16 report from the US House Select Committee on the CCP titled “DeepSeek Unmasked.” The committee labeled the company a national security risk.
Committee Chairman John Moolenaar stated, “This report makes it clear: DeepSeek isn’t just another AI app — it’s a weapon in the Chinese Communist Party’s arsenal, designed to spy on Americans, steal our technology, and subvert U.S. law.”
Open Source Amidst Allegations
The House Committee report detailed serious allegations, claiming DeepSeek funnels American user data back to China via infrastructure connected to state-owned China Mobile and potentially integrates tracking tools from ByteDance and Tencent, citing research from cybersecurity firm Feroot Security.
The committee also alleged DeepSeek acquired “tens of thousands” of advanced chips, potentially violating US export laws, and requested Nvidia disclose sales information to certain Asian nations to track end users. Furthermore, the report highlighted intellectual property concerns, referencing testimony from OpenAI and findings from Microsoft security researchers suggesting DeepSeek personnel may have improperly used techniques like model distillation by circumventing safeguards on US models.
DeepSeek’s continued open-source releases, including Prover V2, and its competition with domestic rivals like Alibaba (which released its Qwen 3 models on April 28, 2025), occur directly in the shadow of these substantial security and geopolitical challenges.
