AI 产业跟踪：OpenAI 发布 GPT-5.2-Codex 智能体编码模型，关注大模型后续迭代发展

Investment Rating - The investment rating for the industry is "Positive" and is maintained [7] Core Insights - On December 19, OpenAI released GPT-5.2-Codex, which is built on the general model GPT-5.2 and optimized for "Agentic Coding" scenarios, primarily targeting complex software engineering tasks. The new model has systematic improvements in long-range task execution, large-scale code changes, Windows native environment support, and network security capabilities compared to previous versions. The commercialization of large models is expected to accelerate, with current costs being a core factor limiting token consumption. Attention should be paid to the cost reduction effects of large models [2][5][9] Summary by Sections Event Description - OpenAI's GPT-5.2-Codex is specifically optimized for complex software engineering tasks, showing systematic improvements in long-range task execution, large-scale code changes, and Windows native environment support [5][6] Performance Insights - GPT-5.2-Codex introduces a native context compression mechanism, enhancing understanding and utilization efficiency for long contexts, making it more stable for long-term coding tasks. The model shows improved performance in code refactoring and migration scenarios, with enhanced reliability and consistency [9] - In terms of network security, GPT-5.2-Codex is the strongest Codex model from OpenAI, demonstrating excellent performance in various security tests, although it has not yet reached the highest risk threshold. The model's capabilities can meet legitimate protection needs while avoiding excessive risks [9] - The model's performance metrics include an accuracy of 56.4% in SWE-BenchPro and 64.0% in Terminal-Bench2.0, indicating a significant improvement in reasoning token efficiency, making it suitable for long-term coding tasks with broad commercialization prospects [9] Future Outlook - The report emphasizes the importance of monitoring future model releases and the need to focus on cost reduction effects for commercialization. The domestic AI industry chain is viewed positively, with continued recommendations for shovel stocks and major players with significant positioning advantages [9]