Core Insights - DeepSeek is leveraging NVIDIA's GPU capabilities while adapting to domestic chips, potentially reducing memory usage by up to 75% and decreasing reliance on imported advanced GPU chips [1][34][39] - The release of DeepSeek V3.1 marks a significant step towards the Agent era, showcasing a hybrid reasoning architecture that supports both thinking and non-thinking modes [3][10] - The upgrade enhances DeepSeek's efficiency, allowing it to answer questions using fewer tokens and less time, improving user experience and economic considerations [4][6] Technical Developments - DeepSeek V3.1 utilizes UE8M0 FP8 scale parameter precision, which significantly reduces memory and bandwidth requirements, thus improving training and inference efficiency [11][15][30] - The model has undergone extensive retraining with an additional 840 billion tokens, achieving a context length of 128k [7][10] - The API Beta interface now supports strict function calling, enhancing reliability and usability in enterprise applications, aligning with trends seen in other major AI companies [8][9] Market Implications - The advancements in DeepSeek's technology are expected to invigorate the Chinese capital market, reflecting a growing focus on technological self-sufficiency [2] - As domestic GPU manufacturers adopt FP8 precision, the demand for NVIDIA's H20/B30 chips may decline, especially if the next generation of domestic GPUs can efficiently run large models [36][38] - The shift towards UE8M0 and ultra-low precision training could lead to a gradual reduction in reliance on NVIDIA's ecosystem, fostering a more independent Chinese AI chip and model landscape [42] Competitive Landscape - Despite the innovations from DeepSeek, NVIDIA maintains its competitive edge with superior bandwidth, interconnect capabilities, and a robust software ecosystem [40][41] - The ongoing evolution of low-precision digital representation technology, as exemplified by DeepSeek's UE8M0, may accelerate the development of next-generation domestic chips [39][42] - The industry is witnessing a potential shift where companies may prioritize domestic solutions over NVIDIA's offerings, particularly in cost-sensitive scenarios [38][42]