Seek .(US:SKLTY) 智通财经网·2025-09-29 10:53Core Insights - DeepSeek officially released the experimental version DeepSeek-V3.2-Exp on September 29, which introduces a sparse attention architecture aimed at optimizing training and inference efficiency for long texts [1][2] - The new model has been integrated into various platforms including the official app, web, and mini-programs, with a significant reduction in API costs for developers [1] Group 1 - The DeepSeek-V3.2-Exp model builds on the V3.1-Terminus version and incorporates a fine-grained sparse attention mechanism called DeepSeek Sparse Attention (DSA), which enhances long text training and inference efficiency without compromising output quality [1] - The model is now available on Huawei Cloud's Model as a Service (MaaS) platform, utilizing a large EP parallel deployment scheme to optimize context parallel strategies while maintaining latency and throughput performance [1] Group 2 - The DeepSeek team conducted a rigorous evaluation of the impact of the sparse attention mechanism, ensuring that the training settings of DeepSeek-V3.2-Exp were aligned with V3.1-Terminus, resulting in comparable performance across various public evaluation datasets [2] - The introduction of the new model has led to a significant reduction in API service costs, with developer costs for accessing DeepSeek API decreasing by over 50% under the new pricing policy [2]