Google has commenced the rollout of its latest Gemini 2.0 Flash artificial intelligence (AI) model to the Android version of its chatbot. This development follows the initial release of the Gemini 2.0 family on December 12, which saw the model integrated into the web version of Gemini on the same day. However, mobile users had to wait until now to access this new functionality, which arrives alongside an innovative model switcher feature that empowers users to select their preferred AI model.
Gemini 2.0 Flash AI Model Comes to Android
The introduction of the next generation of Gemini AI models comes nine months after the launch of the Gemini 1.5 series. Google has emphasized that this new family of models boasts enhanced capabilities, including native support for image generation. Currently, users can experiment with the Flash variant, which is the smallest and fastest model in the series, available in an experimental preview.
For those utilizing the Google app for Android version 15.50 beta, two significant updates are on the horizon within the Gemini app. Firstly, the model information displayed at the top of the screen has become interactive. A downward arrow now appears between ‘Gemini’ and ‘1.5 Flash’ for free users, serving as the model switcher. This feature has been verified by staff members at Gadgets 360.
The second notable enhancement is the introduction of the Gemini 2.0 Flash experimental model. By tapping on the model switcher, users will see a bottom sheet that lists the available AI models for selection. Free users will have access to both the 1.5 Flash and 2.0 Flash models, while subscribers to Gemini Advanced will also be able to choose the 1.5 Pro model.
It is important to note that Google has indicated the Gemini 2.0 Flash is currently available as an early preview and may not function flawlessly. Furthermore, some features of Gemini may not be compatible with this AI model until a full version is launched.
Upon its introduction, Google asserted that the Gemini 2.0 Flash model surpassed the 1.5 Pro model in various benchmarks during internal testing. These benchmarks include the Massive Multitask Language Understanding (MMLU), Natural2Code, MATH, and Graduate-Level Google-Proof Q&A (GPQA).
