DeepSeek-V3.1

DeepSeek-V3.1 functions as a large hybrid reasoning model, utilizing a 671B parameter architecture with 37B active parameters to balance power and efficiency. It is designed to serve as a versatile tool for the agent era, featuring a dual-mode architecture that allows users to toggle between thinking and non-thinking inference paths. This design intent focuses on providing both rapid, direct responses and deep, multi-step reasoning, supported by a 128K context window that enables the model to handle extensive information for complex search and analysis tasks.

The model lineage builds upon the foundation of the V3 family, incorporating continued pre-training on 840B tokens to extend context capabilities and refine overall stability. Post-training enhancements have specifically targeted agentic performance, resulting in measurable gains in tool use, code generation, and terminal-based benchmarks. By addressing earlier challenges with multilingual consistency and character handling, the model provides a more reliable experience for multi-step agent workflows and strict function calling, positioning it as a robust choice for developers building sophisticated, task-oriented AI applications.