Deepseek 3.2

DeepSeek V3.2 continues the main DeepSeek V3 lineage, using a large Mixture-of-Experts (MoE) architecture that activates only part of the model per token, enabling high capacity with efficient compute usage.
It is trained on a large and diverse dataset to provide reliable performance for everyday tasks such as conversation, content generation, translation, analysis, and coding.
The model is built to be stable, predictable, and broadly capable without specializing too heavily in long-context or extreme reasoning scenarios. It is well-optimized for general LLM use cases where consistency, versatility, and reliability matter.
DeepSeek V3.2 is ideal for applications needing solid overall capability rather than specialized optimization. It performs well in reasoning, writing, summarization, creative tasks, technical explanations, and code assistance while keeping inference cost reasonable.