Recently, the Gemini 2.5 Pro model launched by Google DeepMind has attracted widespread attention in the technology industry. As one of the leading AI large language models in the current market, Gemini 2.5 Pro demonstrates unprecedented application potential with its ability to handle extremely long context. However, despite its technological advancement, the operational cost of the model remains high, and there is still room for improvement in terms of quality.
The core competitiveness of the Gemini series lies in its ability to process ultra-long contexts, which makes it particularly outstanding in fields such as AI programming and information retrieval. Compared to other models, Gemini 2.5 Pro can read the entire project content at once, offering a more smooth and efficient user experience. The emergence of this technology marks a new stage in large models, and the application of long context may potentially change traditional ways of information interaction.
In a conversation with podcast host Logan Kilpatrick, Nikolay Savinov, a research scientist at Google DeepMind, emphasized the importance of context. He pointed out that the context information provided by users can significantly enhance the personalization and accuracy of the model. The model does not rely solely on pre-trained knowledge but also depends on users' real-time input to update and adjust its responses, ensuring the timeliness and relevance of the information.
Savino also mentioned that RAG (Retrieval-Augmented Generation) technology will not be phased out, but instead will work in conjunction with long context. This technology helps the model quickly retrieve relevant information from a vast knowledge base through preprocessing steps, thereby further improving the recall rate of information on top of millions of context. When combined, both technologies can significantly improve the performance of the model in practical applications.
The future prospects of long-context technology are very optimistic. With the gradual reduction in costs, it is expected that the ability to handle tens of millions of context will become an industry standard in the near future. This undoubtedly brings revolutionary breakthroughs in AI coding and other application scenarios.
Gemini 2.5 Pro not only advances AI technology but also opens up new possibilities for enhancing user experience. The application of long context and its integration with RAG technology indicate that the future of AI will be smarter and more personalized.
