DeepSeek新模型正式发布！寒武纪已实现适配

Core Insights - DeepSeek has officially released the DeepSeek-V3.2-Exp model, which introduces a Sparse Attention mechanism for improved training and inference efficiency on long texts [1] - The official app, web version, and mini-program have all been updated to DeepSeek-V3.2-Exp, with a significant reduction in API costs by over 50% for developers [1] - The company has also adapted to the latest DeepSeek model and open-sourced the vLLM-MLU inference engine code, allowing developers to experience the new model on their platform [1] Model Iteration and Features - DeepSeek is progressing with model iterations, having recently upgraded to DeepSeek-V3.1-Terminus, which features a hybrid inference architecture supporting both thinking and non-thinking modes [2] - The V3.1 model boasts higher thinking efficiency and enhanced agent capabilities, showing significant improvements in tool usage and intelligent task performance [2] - The V3.1 model utilizes UE8M0 FP8 Scale parameter precision, designed for the upcoming generation of domestic chips, which has positively impacted the stock prices of related domestic chip industry companies [2]