GPT-5.2系列发布：重新定义AI生产力，驱动AI从模型竞争转向场景落地

Investment Rating - The report assigns an "Overweight" rating for the industry, indicating an expected performance exceeding the CSI 300 Index by more than 15% [4]. Core Insights - The release of the GPT-5.2 series marks a significant transition from showcasing AI capabilities to creating economic value, highlighting the potential of AI in high-end professional fields [2][4]. - GPT-5.2 achieves human expert-level performance in abstract reasoning and complex knowledge tasks, with a score of 52.9% in the ARC-AGI-2 test, a nearly threefold increase from GPT-5.1's 17.6% [4]. - In the GDPval benchmark, GPT-5.2 Thinking outperformed or matched industry experts in 70.9% of tasks, while GPT-5.2 Pro reached 74.1%, indicating a historic achievement in comprehensive knowledge work assessments [4]. - The model shows significant improvements in code generation, long-context processing, and visual understanding, with a near 100% accuracy in a 256K token length test, compared to 30% for GPT-5.1 [4]. - GPT-5.2's tool invocation reliability has improved, achieving a score of 98.7% in complex multi-step tasks, demonstrating strong end-to-end task execution capabilities [4]. Summary by Sections Investment Recommendations - The report emphasizes that the GPT-5.2 series signifies a new phase in the scalability of AI capabilities, shifting the focus of industry competition towards specific application scenarios and enterprise services [4]. Performance Metrics - The report details that GPT-5.2's performance in financial modeling tasks improved from an average score of 59.1% to 68.4%, indicating deeper penetration of AI into core productivity processes [4]. - The model's advancements in visual tasks reduced error rates by nearly half compared to previous versions, enhancing its spatial reasoning capabilities [4]. Deployment Strategy - OpenAI's deployment strategy includes offering the GPT-5.2 series to paid users while maintaining GPT-5.1 for a smooth transition, despite a 40% price increase for the API, which is justified by improved token efficiency [4].