Today, OpenAI officially launched its highly anticipated new GPT-5 series model, a milestone release that has quickly caused a stir in the industry. Almost simultaneously, Microsoft announced the deep integration of GPT-5 into its core platforms such as Copilot, Microsoft 365 Copilot, Azure AI Foundry, and GitHub Copilot, marking the official arrival of GPT-5 in the Microsoft ecosystem and offering users an unprecedented upgrade in intelligent experience.
The GPT-5 series model introduces an innovative smart mode that can automatically switch to the appropriate model version based on user task requirements. When dealing with complex tasks, the system will automatically call the version with stronger reasoning capabilities; in scenarios requiring fast response, it will prioritize the faster model. This dynamic adjustment mechanism significantly enhances usage efficiency and flexibility. Notably, OpenAI has already made GPT-5 available to free ChatGPT users. Microsoft has also continued this strategy, allowing Copilot users to experience the powerful features of this model without additional charges.
The developer community has also received significant benefits. GitHub announced support for GPT-5 for all paid GitHub Copilot users, allowing developers to immediately test the performance breakthroughs of the new model in scenarios such as code generation and logic optimization. According to reports, the GPT-5 series includes four sub-versions, with the main version focusing on multi-step logical task processing, while GPT-5-chat is designed for enterprise-level conversation needs, featuring multimodal interaction and context awareness, enabling a more natural intelligent conversation experience.
In terms of infrastructure, Microsoft has introduced GPT-5 into Azure AI Foundry, allowing developers to directly call this cutting-edge model in AI application development. Through the built-in intelligent model router, the Azure platform can automatically match the optimal model version based on task characteristics, ensuring effectiveness while maximizing execution efficiency. This innovative architecture provides solid technical support for the large-scale deployment of AI applications.