DeepSeek V4 Pro is a large-scale Mixture-of-Experts language model built to handle complex reasoning and technical workflows. With 1.6 trillion total parameters and 49 billion active parameters per token, it is engineered to deliver performance that rivals top-tier closed-source models. The architecture features a hybrid attention mechanism that combines Compressed Sparse Attention and Heavily Compressed Attention, allowing the model to maintain a one-million-token context window with significantly improved efficiency. By incorporating Manifold-Constrained Hyper-Connections, the design ensures stable signal propagation, making it particularly effective for demanding tasks in mathematics, STEM, and agentic coding.

The model lineage focuses on achieving high-efficiency intelligence at scale, utilizing structural innovations to reduce inference costs and computational overhead. By requiring only a fraction of the FLOPs and KV cache compared to its predecessors, the model provides a practical solution for developers needing deep reasoning capabilities without the typical resource intensity. Its design is optimized for complex agentic workflows, positioning it as a leading open-weight choice for users who require high accuracy in coding and world knowledge. As a versatile tool for technical decision-makers, it serves as a bridge between high-end reasoning performance and cost-effective, long-context deployment.