DeepSeek V3.1 is positioned as the lab's first step toward an agent-focused era, built on a large Mixture-of-Experts backbone of 671 billion parameters with about 37 billion activated per inference. The defining design choice is hybrid inference in a single model: users can toggle a "DeepThink" button in the chat UI or pick between deepseek-chat for non-thinking responses and deepseek-reasoner for thinking-mode answers, both served through a 128K-token context window. Continued pretraining on roughly 840 billion tokens extends long-context behavior on top of the earlier V3 base, and post-training shifts the model toward stronger tool use and multi-step agent workflows rather than only chat-style generation.

In practice, the hybrid shape lets the same weights handle fast, conversational replies and deeper analytical chains, which is useful for code generation, structured search tasks, and orchestrated agent pipelines. The release highlights better results on software-engineering style evaluations like SWE-bench and Terminal-Bench, alongside gains in thinking efficiency compared with the previous R1-0528 checkpoint, and Together AI echoes the framing by marketing the model as an advanced reasoning system aimed at reasoning, coding, and agent tasks. The official API additionally exposes an Anthropic-compatible interface and a strict function-calling beta, while independent hosts route the same weights through their own endpoints, making the model a flexible foundation for teams that want open weights with production-style serving options.