Gemini for Android Gets New Model Switcher Feature, Gemini 2.0 Flash Option

Google has started rolling out the new Gemini 2.0 Flash artificial intelligence (AI) model to the Android app of the chatbot. The Mountain View-based tech giant released the first model in the Gemini 2.0 family on December 12. While the model was added to the web version of Gemini on the same day, the mobile apps did not get access to it immediately. However, it has now started rolling out to users, along with a new model switcher feature that lets users pick and choose the AI model.

Gemini 2.0 Flash AI Model Comes to Android

The next generation of Gemini AI models was announced nine months after the arrival of the Gemini 1.5 series. Google said that the new family of models offer improved capabilities, including native support for image and generation. Currently, only the Flash variant is available, which is the series' smallest and fastest model. It is currently available in an experimental preview.

Model switcher feature in the Gemini app

Those on the Google app for Android version 15.50 beta will soon see two changes in the Gemini app. First, the model information added at the top of the screen is now tappable. A downward arrow now appears between ‘Gemini' and ‘1.5 Flash' for the free users. This can be used as the model switcher. Gadgets 360 staff members were able to verify the new feature.

The second change is the addition of the new Gemini 2.0 Flash experimental model. Once a user taps on the model switcher, a bottom sheet appears listing the available AI models to choose from. While free users will only see 1.5 Flash and 2.0 Flash, those subscribed to Gemini Advanced will also see the 1.5 Pro model.

Notably, Google had highlighted that the Gemini 2.0 Flash is available as an early preview and might not work as expected. Additionally, some Gemini features might not be compatible with the AI model till a full version is released.

At launch, Google claimed that Gemini 2.0 Flash outperformed the 1.5 Pro model in several benchmarks during internal testing. Some of the benchmarks include the Massive Multitask Language Understanding (MMLU), Natural2Code, MATH, and Graduate-Level Google-Proof Q&A (GPQA).