What Is Gemini? Multimodal Models and App Features
Gemini is a Google model family and the name of its consumer app. Using Gemini 4 Argon as an example, this article explains input and output modalities, context limits and the distinction from Gemma.
Meet this model
Gemini is Google’s generative AI model family, with particular versions accepting text and multiple media types. Gemini Apps is the application for chatting and uploading files. Multimodality must distinguish input types from generated content. For example, Gemini 4 Argon accepts audio and video but outputs text; understanding video does not imply generating it. Readers seeking local model weights should also distinguish the separate Gemma family.
The app name does not identify a model configuration
In Gemini Apps, available features depend on the account and product availability. Developers using the Gemini API or an applicable cloud service must also choose a model code. File upload in the app does not imply that every earlier model accepts the same file types, and app limits should not be treated as API limits.
The October 20, 2026 catalog includes Gemini 4 Argon and several Flash models, with separate entries for speech and image generation. The family spans many tasks. To narrate a script, choose a specific model that supports audio output. Selecting a general text reasoning model may produce no audio file at all.
Argon illustrates specific multimodal boundaries
Argon’s model card lists text, image, video, audio and PDF input, with text output. It supports features including function calling and search grounding, while explicitly excluding image generation and the Live API. Audio input support alone does not establish that this model is suitable for a real-time voice assistant.
Its unified context limit is 1,048,576 tokens, shared by input and output. The default synchronous output limit is 65,536 tokens, with a separate mechanism for longer output. When processing a long report, do not treat the context size as a promise of an equally long response. Leave room for the answer.
Choosing for document work or self-hosting
For a text outline of a training video, request a timestamp for each conclusion and check brief actions against the original recording. Compare models using the same clips and questions, recording omissions and incorrect attributions separately. This article reviews official specifications and does not test video-understanding accuracy or real response speed.
The Gemini API is provided under its additional service terms. API access is not local weight access. Gemma is Google’s separately released open-weight model family, with deployment and licensing determined by the specific version. Despite similar names, applying a Gemini app tutorial to Gemma does not give a local inference environment the cloud product’s features.
Checked sources
These sources support the concepts and methods described here. Examples and test scope are labeled separately; check the version of the tools you use.