Google Gemini
Updated for version: December 2025
Accessible via: https://gemini.google.com/app
Requires login via: Google
Ratings
Accuracy / Quality ★★★☆☆
Flexibility / Features ★★★★☆
Data security / Privacy ★★☆☆☆
Pros/cons
Pros
- Free building and sharing of AI agents
- Possible to opt out of training on user data
- Internet access
- Image recognition and generation
- Voice input
- Shortcut to check answers with Google search
Cons
- Substantial hallucination rate
Description
This Large Language Model (LLM) uses the Gemini 3 model with Vision and Voice integration to function. There is a more advanced model available, but this is locked behind a subscription. The accuracy of this model depends on the type of question asked, with a higher accuracy for more basic questions or questions which can be answered using recent information from internet sources. Having the ability to also interpret images and voice does expand its functionality, but the model cannot output any images or sounds. The ability to add sources / validate the output of the model against a typical Google search does add a small level of reliability to the output. And the various draft versions of the output allows for greater variation in the responses.
Gemini was trained on a large amount of data collected from various sources available online, which may include the use of data without the author’s permission. Gemini will also train on the user’s input, which cannot be disabled by the user, making it less data-safe than some of its competitors.
Features and examples
Gems
Gemini now also allows you to build custom AI agents. In Gemini, these agents are called Gems. Gems are free to use, and can also be shared with others for free. Learn more about building AI agents in this knowledge base.
Google search
Continuing with our example of the lab-grown meat, we asked the model to check its response against the results obtained through a Google search.
The model then searches for information related to the answer previously given, and adds both a source and a colour code to the output. The source indicates where it received its answers from, and the colour code indicates whether the model was able to find corroborating information (green) or conflicting information (orange). It is still the user’s responsibility to validate the sources and the information, but this can be a helpful tool to help identify some of the more questionable statements.
Please note the source is not always a scientific paper or otherwise reliable source. Hence it is important to always validate both the stated information as well as the reliability of the source provided.
In the example given, one statement was found to conflict with the typical response given by a Google search, and was flagged for user review.
Data controls
In Gemini, you can disable training on your data, by clicking on Activity in the menu on the left side of your screen. In the Keep Activity menu, you can adjust the time for which your data is saved by Google.
After turning this off, Google will no longer store your information to improve the model.
