论文分析：DeepSeek R1 与 Kimi K3 发布引发的金融市场反应差异
The Reaction of Financial Markets to the Releases of DeepSeek R1 and Kimi K3: A Critical Analysis
这篇论文把 DeepSeek R1 和 Kimi K3 发布时的股价反应放在一起比，解释了为什么两次市场反应完全不同，做投资或研究行业的人都该看看。
一篇 arXiv 论文对比了 DeepSeek R1（2025 年 1 月发布）与 Kimi K3（2026 年 7 月发布）对金融市场的不同影响。DeepSeek R1 因开源权重加上极低的训练与推理成本，导致半导体和数据中心相关股票大幅下跌。Kimi K3 以接近前沿的价格发布，市场反应则集中在其他中国 AI 实验室的股价上。论文认为开源权重模型是在 AI 价值链中重新分配租金，而非消灭租金，在位企业仍受分发渠道、产品捆绑、专有数据等互补资产保护。
The Reaction of Financial Markets to the Releases of DeepSeek R1 and Kimi K3: A Critical Analysis
This paper compares financial-market reactions to the releases of DeepSeek R1 in January 2025 and Kimi K3 in July 2026. Both AI models were presented as credible Chinese competitors near the capability frontier, but their releases conveyed different economic information. DeepSeek R1 combined open weights with unusually low reported training and inference costs, prompting investors to reassess expected demand for computing infrastructure and producing large stock-price decreases among semiconductor and data-centre-related firms. Kimi K3 instead entered at broadly frontier prices and generated a market reaction concentrated more heavily among rival Chinese AI laboratories. Drawing on descriptive event-window evidence, model capability and cost comparisons, subsequent industry developments, and the historical diffusion of open-source software, the paper argues that open-weight models redistribute rents across the AI value chain rather than eliminating them. Incumbents remain protected by complementary assets including distribution, product bundling, switching costs, proprietary data, serving capacity, and contractual trust. The analysis suggests that investors and policy makers should assess risks looking not only at model capability, but also at the ownership and durability of complementary assets across the AI value chain.
