Ask most people what Google's AI is called and they'll say Gemini. That's accurate, but incomplete. In 2026, Gemini is the engine at the center of an ecosystem that spans text, image, video, music, code, autonomous agents and smart home integration. Understanding how the pieces fit together matters for anyone who wants to use these tools effectively — whether as an individual, a developer or a business.
Gemini: the model family at the core
Everything starts with Gemini, developed by Google DeepMind — the research lab that emerged from the merger of Google Brain and DeepMind in 2023 and now concentrates the bulk of Google's AI research effort.
The Gemini family in 2026 has four main variants, each built for a different context:
Gemini Nano is the smallest. It runs directly on the device — no internet connection required — and powers AI features built into Android: notification summaries, unsafe audio detection, on-call assistance. It's deliberately lightweight, prioritizing speed and privacy over complex reasoning.
Gemini Flash is the high-volume workhorse. Fast, cost-efficient, and capable of handling up to a million tokens of context, it's what most developers use via the API for chatbots, automated summaries and content classification. Gemini 3 Flash is the most recent version in this line.
Gemini Pro is the general-purpose model with advanced reasoning. It powers the standard chat experience at gemini.google.com and is the most widely used model via API for deep analysis, long-form content generation and multimodal comprehension. Gemini 3.1 Pro is the latest iteration, with improvements in instruction-following and reduced hallucination rates.
Gemini Ultra is the most powerful model in each generation. It's designed for complex reasoning, advanced mathematics, science and deep research. It includes Deep Think, an extended reasoning mode that allows the model to take more time on difficult tasks in exchange for more accurate answers.
Gemini Pro's context window reaches one million tokens — roughly equivalent to 1,500 pages of text or 30,000 lines of code — putting it among the highest-capacity document-processing models available.
Nano Banana 2: Google's image generator for everyone
One of the most distinctive tools in the ecosystem has a name that stands out: Nano Banana 2. It's Google's most recent and advanced image generation model, available directly from the Gemini app at gemini.google.com. According to Google's own description, it combines advanced knowledge, quality and reasoning to bring visual ideas to life with greater precision than previous versions.
Unlike Imagen 4 — which is aimed at developers via API in standard, Ultra and Fast variants — Nano Banana 2 is built for the end user, accessible from the Gemini interface without any code or technical setup. It's the equivalent of what DALL·E is for ChatGPT, but natively embedded in Google's ecosystem.
Veo 3.1: video with sound, dialogue and effects
For video generation, Google has Veo. The most recent version, Veo 3.1, generates clips of up to 8 seconds from text or image prompts, with support for synchronized audio, spoken dialogue, background music and sound effects. It's the most complete generative video model in terms of integrated audio production currently available.
Veo 3.1 is available to developers on the paid tier of the Gemini API and to Ultra plan subscribers in the app. In Whisk, Pro plan users can turn static images into short videos using Veo 3 as the underlying engine.
Flow: AI filmmaking for serious creators
Flow is Google's entry into professional audiovisual production. It's a filmmaking suite that brings together the three creative models in the ecosystem — Veo, Imagen and Gemini — into a single interface designed for directors, producers and content creators.
It supports text-to-video, ingredient-to-video (combining characters, scenes and styles as visual prompts) and frame-to-frame generation. Pro plan users receive monthly AI credits for Flow, and the Ultra plan significantly expands that capacity.
NotebookLM: the research tool that keeps getting better
NotebookLM started as a note-taking assistant and has evolved into one of the most sophisticated AI research tools available. Users can load up to 300 sources per notebook — documents, PDFs, YouTube videos, web pages, audio recordings — and then query them, request summaries, generate audio overviews and create presentations.
Google AI Pro unlocks the advanced features: up to 500 notebooks, 300 sources per notebook, 500 daily queries and more audio generation capacity. It's particularly valued by researchers, journalists, lawyers and anyone who regularly works with large volumes of information.
Jules, Gemini CLI and Antigravity: the developer stack
Google offers three distinct tools for developers and engineers:
Jules is the asynchronous coding agent. Unlike a copilot that suggests lines of code in real time, Jules works independently: it receives a task, analyzes the codebase, proposes an action plan and executes it without constant supervision. Think of it as a junior developer that can handle specific tasks autonomously.
Gemini CLI brings AI directly into the terminal. It lets developers run queries, generate code, analyze files and manage development tasks from the command line — no browser or graphical interface required.
Antigravity is Google's next-generation IDE, available at antigravity.google. It's designed for developers who want to integrate AI natively into their programming workflow, with Windows support and direct download from the official site.
Project Mariner: the agent that browses for you
Project Mariner is one of Google's most ambitious agent projects. It delegates full tasks to an agent operating inside the browser: planning a trip, making reservations, filling out forms, placing orders online. The agent interacts with real websites the same way a human user would — not through APIs, but through the actual interface.
Ask Maps: the biggest Maps update in years
Gemini's integration into Google Maps produced Ask Maps, a conversational search interface for finding places. Instead of typing "restaurants near me," users can ask natural-language questions with context and constraints and receive suggestions that account for all of them. Google has described it as the most significant update to Maps in over a decade.
What it costs
Access to Google's AI ecosystem comes in three tiers:
The free plan includes Gemini Flash, basic features and access to Nano Banana 2 for image generation directly from the Gemini app — more than enough for personal use and experimentation.
Google AI Pro costs $19.99 per month (with a free first month) and includes Gemini 3, Deep Research, around 1,000 monthly AI credits for Flow and Whisk, limited Veo 3 video generation, enhanced NotebookLM with up to 500 notebooks and 500 daily queries, and Gemini integration across Gmail, Docs, Drive, Sheets and Meet.
Google AI Ultra costs $124.99 for three months and adds Gemini 3 Pro, close to 25,000 monthly AI credits, full Veo 3.1 access, maximum NotebookLM capacity and Deep Think for extended reasoning on the most demanding tasks.
Why the ecosystem matters more than any single model
What sets Google apart from other AI competitors is not necessarily having the best model in any single category — it's the depth of integration across products that hundreds of millions of people already use every day. Gemini is inside Gmail, Drive, Maps, Android, Chrome, the smart home and web search. That ubiquity is both Google's greatest strength and its hardest-to-replicate advantage for any competitor starting from scratch.
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