Gemini is Google DeepMind's family of multimodal AI models that can process and generate text, images, audio, video, and code, and it also refers to Google's consumer chatbot app built on those models.

When was Gemini released?

Gemini launched in December 2023, replacing Google's earlier Bard chatbot as the company's flagship conversational AI product.

How is Gemini different from ChatGPT?

Both are large language model chatbots, but Gemini was designed from the ground up to be multimodal and integrates tightly with Google's ecosystem, including Search, Workspace, and Android, while ChatGPT is developed by OpenAI and integrates with Microsoft products.

Is Gemini free to use?

Google offers a free tier of the Gemini app with usage limits, alongside paid subscription plans that unlock more advanced models, higher usage limits, and additional features.

Can developers build with Gemini?

Yes. Developers can access Gemini models through the Gemini API and Google AI Studio for prototyping, or through Vertex AI for enterprise-grade deployment, fine-tuning, and governance.

What does 'multimodal' mean for Gemini?

It means Gemini can accept and reason about multiple input types — text, images, audio, and video — in the same conversation, rather than requiring separate specialized models for each type.

Does Gemini power Google Search?

Yes, Gemini models underpin AI Overviews and other AI-assisted features in Google Search, summarizing information and answering questions directly in search results.

What are the different Gemini model sizes for?

Google offers Gemini in multiple sizes, generally trading off capability for speed and cost — larger models handle complex reasoning tasks, while smaller, faster models are used for real-time or on-device applications.

AI Models

Gemini

By Google DeepMind

BeginnerModel5.1K learners

Gemini is Google's family of multimodal large language models, built by Google DeepMind, that understands and generates text, images, audio, video, and code within a single model architecture. It powers Google's consumer chatbot (also…

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Definition

Overview

Gemini launched in December 2023 as the successor to Google's earlier Bard chatbot and PaLM 2 models, unifying Google's AI research under one model family developed by Google DeepMind after the 2023 merger of Google Brain and DeepMind. Unlike models that bolt on multimodality after the fact, Gemini was trained from the outset to reason jointly across text, images, audio, video, and code, which is the main technical distinction Google draws against rivals like ChatGPT. Gemini ships in several size tiers — typically Ultra/Pro-class models for complex reasoning and Flash/Nano-class models for speed and on-device use — so developers can trade off cost, latency, and capability. Later generations (Gemini 1.5, 2.0, 2.5) introduced very long context windows capable of processing hours of video or hundreds of pages of documents in a single prompt, along with native tool use, code execution, and agentic capabilities. Google distributes Gemini through several surfaces: the consumer Gemini app and web chat, integration into Search (AI Overviews) and Workspace apps like Docs and Gmail, the Gemini API for developers, and enterprise access via Vertex AI and Google AI Studio. This positions Gemini as a direct competitor to Claude, ChatGPT, and Grok across both consumer and enterprise AI markets, and learners exploring how these systems work can start with the Large Language Models course.

Key Features

Natively multimodal architecture spanning text, images, audio, video, and code
Multiple model sizes (Pro, Flash, Nano-class) for different latency and cost needs
Very long context windows supporting large documents, codebases, or video input
Deep integration with Google Search, Workspace, and Android
Gemini API and Google AI Studio for prototyping and app development
Enterprise access and fine-tuning through Vertex AI
Built-in tool use, code execution, and agentic task capabilities

Use Cases

Conversational assistance for research, writing, and everyday questions

Summarizing and drafting content inside Gmail, Docs, and Sheets

Multimodal analysis — interpreting screenshots, PDFs, charts, and video

Coding help, including code generation, explanation, and debugging

Enterprise chatbots and agents built on Vertex AI

AI-powered search overviews and question answering in Google Search

On-device AI features on Android via smaller Nano-class models

Frequently Asked Questions

From the Blog

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