The reactions 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 training and inference costs reported, prompting investors to reassess the demand expected 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 that was more heavily concentrated 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. The 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 by looking not only at model capability, but also at the ownership and durability of complementary assets across the AI value chain.