DeepSeek V3.1 is a hybrid large language model released by DeepSeek in August 2025 as an iterative upgrade to the DeepSeek-V3 architecture. It is characterized by its dual-mode capability, allowing users to switch between a Non-Thinking mode for direct answers and a Thinking mode for complex reasoning tasks. The thinking mode utilizes chain-of-thought processing to handle intricate logical, mathematical, and coding challenges with increased efficiency compared to earlier reasoning-specialized models.
Built on a Mixture-of-Experts (MoE) framework, DeepSeek V3.1 contains 671 billion total parameters, of which approximately 37 billion are active during any single inference step. This architecture enables the model to maintain high performance across a wide range of domains while optimizing computational costs. The model also incorporates Multi-head Latent Attention (MLA) and was trained using the UE8M0 FP8 data format for improved memory and processing efficiency.
The V3.1 update significantly enhances the model's performance in agentic workflows and tool usage through targeted post-training optimizations. It supports an expanded context window of 128,000 tokens, making it suitable for long-document analysis and multi-step task execution. In reasoning benchmarks, the model's thinking mode is designed to match the output quality of specialized reasoning models like DeepSeek-R1 while delivering faster response times.