Core Insights - DeepSeek company has released the DeepSeek-V3.2-Exp model, introducing a sparse attention mechanism that significantly reduces computational resource consumption and enhances inference efficiency [1][6] - The new model has led to a price reduction of API services by 50% to 75% [1] - The release has prompted immediate recognition and adaptation from several domestic chip manufacturers, including Huawei, Cambricon, and Haiguang, indicating a growing synergy within the domestic AI hardware and software ecosystem [2][4] Summary by Sections Model Release and Features - The DeepSeek-V3.2-Exp model incorporates the DeepSeek Sparse Attention mechanism, optimizing training and inference efficiency for long texts [6] - The model is compatible with CUDA and utilizes TileLang for rapid prototyping, which is designed specifically for AI operator development [6] Industry Response - Cambricon was the first to claim adaptation of the new model, followed by Huawei and Haiguang, showcasing a collaborative effort among domestic manufacturers [2] - The rapid response from these companies indicates a consensus within the domestic AI industry regarding the significance of the DeepSeek model [6] Ecosystem Development - DeepSeek is emerging as a key player in building a new ecosystem for domestic AI, with its model becoming a benchmark for open-source models in China [2][4] - The collaboration among major internet companies like Tencent and Alibaba in adapting domestic chips further accelerates the establishment of this ecosystem [7] Historical Context - The previous version, DeepSeek-V3.1, did not receive any proactive claims from companies regarding its adaptation, highlighting the significant shift in industry dynamics with the latest release [5] - Experts believe that the rapid development of domestic chips by 2025 can be attributed to the emergence of DeepSeek as a standard-setting entity [3]