Gemini does not know anything beyond Gemini 1.5 exists and cannot tell me how to use the API

Understanding the Limitations of Gemini AI Models and API Integration Challenges

In recent experiences with Gemini AI models, users have encountered significant limitations regarding model awareness and API functionality, particularly with the newer versions like Gemini 2.5 Pro.

Despite enabling Google Search integration within AI Studio, users report that various Gemini models—including Gemini 2.5 Pro, Flash Lite Preview, and others—fail to provide accurate guidance on how to properly utilize the Gemini API parameters. Efforts to consult official API documentation, even supplemented by Google Search, have met with resistance from the AI, which appears to lack awareness of recent updates and is unable to accurately interpret or implement its own API features.

One user recounted attempting to troubleshoot by providing direct links to API documentation and enabling grounded search capabilities, only to face persistent misunderstandings. The AI would erroneously claim that specific features, such as “thinking mode” and “Google Search parameters,” are unavailable or incorrectly implemented. In some cases, the AI even altered the model identifiers in the API requests—changing from “gemini-2.5” to “gemini-1.5″—without any direction from the user, further complicating the troubleshooting process.

These issues highlight notable challenges in working with Gemini models, especially regarding their API parameter management and the AI’s contextual awareness of its own capabilities. As it stands, users are experiencing a disconnect between available documentation and the AI’s responses, leading to frustration and confusion.

For developers and AI practitioners, these experiences underscore the importance of ensuring clear, consistent API documentation and verifying model update propagation. It also suggests that, at present, Gemini models may have limitations in understanding and utilizing their own APIs effectively, necessitating cautious implementation and thorough testing when integrating them into larger workflows.

In conclusion, navigating the Gemini AI ecosystem requires patience and a thorough understanding of its current capabilities and limitations. As the technology evolves, greater clarity and improved model self-awareness will be crucial to facilitate smoother integration and user experience.