DeepSeek V4 Pro is a large-scale Mixture-of-Experts model built to handle demanding reasoning and coding tasks. With 1.6 trillion total parameters and 49 billion active parameters, it is designed to excel in complex workflows such as full-codebase analysis, multi-step automation, and extensive information synthesis. The model features a hybrid attention architecture that combines Compressed Sparse Attention and Heavily Compressed Attention, allowing it to manage a one-million-token context window with high efficiency. This structural design significantly reduces inference costs and memory usage compared to previous generations, making it a robust choice for tasks requiring deep, long-horizon intelligence.

The model incorporates Manifold-Constrained Hyper-Connections to improve signal propagation and stability during operation. By leveraging this architecture, the model achieves performance levels that rival top closed-source systems, particularly in math, STEM, and agentic coding benchmarks. Its design lineage focuses on balancing high-level reasoning capabilities with practical efficiency, positioning it as a versatile tool for developers and enterprises. As an open-weight model, it provides a scalable foundation for advanced agentic workflows, offering a balance of world-class knowledge and computational performance for users tackling sophisticated, data-intensive challenges.