Gemini 3: An Overview of Developments
Before we explain Gemini as an AI application in more detail in general, we have briefly summarized the most important updates in advance. According to Google CEO Sundar Pichai, Gemini 3 allows “to bring every idea to life”, with a particular focus on multimodality, agentic coding, and visual and interactive outputs. Google publishes all updates and news about Gemini and AI products via the Google blog.
Everything you need to know about Gemini at a glance:
What does this mean specifically for users?
For users and companies, Gemini offers improved, multimodal AI support for text, images, voice, music, planning, and scalable enterprise solutions. Developers have more control and flexibility through deep “thinking,” expanded media inputs, structured outputs, and more tool integrations than ever before. This means faster implementation for software projects, e.g. prototypes, using the Gemini app, developer tools and the combination of Antigravity and Gemini 3. The most important trend is the shift towards true agentic AI, so that multi-level tasks are carried out independently by the AI.
What is behind Google Gemini?
Google Gemini comprises a family of multimodal large language models, who can understand and generate texts, images, videos, and programming code themselves. There are two terms in this definition that should be better explained so that you can understand Google Gemini better.
As Large Language Models (LLM for short) In the field of artificial intelligence, neural networks are primarily referred to as neural networks that can understand, process and generate human language themselves in various ways. The term “large” describes the property that these models are trained on vast amounts of data and have several billion neurons or parameters that recognize the underlying structures in the text.
Multimodal models are part of machine learning and include architectures that can process several variants of data, the so-called modalities.
The Most Important Features of Gemini
Google Gemini has become a broadly deployable AI ecosystem and Gemini 3 will be rolled out "at the scale of Google“ — i.e. simultaneously in several core products such as Google Search, Chrome, Workspace and Google Apps. Gemini can generate generative content such as text, images, and videos and combine contextual and personal intelligence with productivity and automation features such as auto-browse and agentic tasks.
Here are a few possible uses of the Gemini models:
- Marketing and content creation: automated texts for posts, captions, campaign planning and image generation
- Productivity and workspace: Summaries of documents, slides, and transcripts with personal intelligence as a connection between Google products
- Research and analysis: Report generation, multimodal analysis and step-by-step task processing
- Coding capabilities: Code generation, debugging and refactoring, and automated application development
Interpretation and Generation With Native Multimodality
Just like GPT-5, OpenAI's comparable model and the currently most used LLM, Google Gemini is multimodal, meaning it can process various types of input, such as texts, images, videos or programming code, and also provide them as output. Gemini was developed from the start, so natively, as a multimodal system, so that complex conclusions and outputs can be generated from a wide variety of input formats. As a result, demanding tasks in areas such as mathematics or physics as well as data-intensive analyses can be completed much more efficiently. In addition, the improved deep-think and multi-expert architecture allows even more precise analysis and problem-solving in several steps.
Gemini can program and provide a finished application simply by analysing an image. This allows websites to be recreated, for example, by giving Gemini a screenshot of the current page. Although a screenshot cannot depict the full complexity of a website or program, it serves as a good starting point for further programming.
Image Generation and Video Creation
At the end of February, Nano Banana 2, the updated model based on the Gemini 3.1 flash image platform, was rolled out. The model has better instructional following and text rendering. Text-to-image prompts provide photorealistic or stylized images based on the individual user request. Users can also combine text and image, for example by using Gemini to generate a new one from two images, including a suitable description. In an example from Google, it is shown how to make a wool octopus from two different coloured balls of wool, supplemented by instructions on how to make it.
In addition, with the integration of Gemini's Veo models, videos can be summarized and key frames extracted. For users of the Google AI Ultra subscription, the advanced Veo 3 model is available, which offers realistic videos and improved sound integration. However, full video generation is not yet available in the standard API. For now, Gemini is focused on analysis, not native generation.
Agentic Capabilities
In 2026, Gemini 3 is clearly positioning itself as an agent system with browser and app control.
Deep Research is a specialized mode in Gemini 3 and represents an agentic research assistant. The web is searched autonomously (including Gmail/Drive) to collect information and create multipage reports with sources, visuals, and YouTube integrations. Agentic workflows are at the focus of development, as they enable autonomous task execution, even for multistep processes. This includes the live web browsing feature, which is integrated with Google apps such as Gmail, Calendar, Drive, Maps.
Gems allow you to create tailor-made assistants, such as a “marketing expert gem” that plans campaigns and optimizes SEO keywords.
With the Live API, Gemini enables real-time conversations with continuous back-and-forth streaming: audio and video inputs are processed live, ideal for voice agents in customer service. Gemini is currently available in over 230 countries and regions and in more than 70 languages. Google AI Pro users can also set Gemini to remember previous conversations. This makes the interaction even more personalized, but the protection of personal data must be taken into account.
Gemini in the Early Days
Google Gemini was unveiled for the first time at a virtual press conference on December 6, 2023. At the same time, both the Google blog and the website of the AI company Google DeepMind went online, which describe the functionalities of the new AI family. Early versions enabled simple code generation, image editing, and the combination of text and image information, among other things. Gemini found its first applications for basic research and learning support. With the introduction of Gemini 2 and subsequent updates, these capabilities have been steadily improved, in particular through deep think modes for multi-stage reasoning, editing longer documents, and analyzing complex mathematical and scientific tasks.
Which Versions of Gemini Are There?
Gemini 3
The ‘Gemini 3’ series, comprising the Flash and Pro variants, was officially launched in November 2025 and has since been Google’s flagship model generation for high-performance AI applications. Gemini 3.5 Flash is the new standard in the Gemini app, and Gemini 3.1 Pro Preview has also been available since February 2026. The roll-out will continue in stages throughout 2026:
- End users can access the models via the Gemini app and through web and browser integrations (including Search and Chrome)
- Developers can use them via the Gemini API, Google AI Studio, Vertex AI and the agent-oriented development environment Google Antigravity
- Businesses and enterprise customers can access them via Gemini Enterprise, subject to admin approvals in the control panel
Alongside the release of Gemini 3, the new development platform Google Antigravity – an agent-first IDE – was unveiled at the end of 2025. The older Generation 2 models will remain available, but individual preview versions will be phased out gradually, and Google is clearly focusing on Gemini 3.
Gemini-3 models support large input context windows of up to 2 million tokens, with intelligent retrieval and storage methods. Noteworthy features include flexible media processing and quality control via the `media_resolution` parameter. The parameter supports the levels ‘low’, ‘medium’, ‘high’ and, newly, ‘ultra_high’. This regulates the resolution at which images and videos are processed. The ‘thinking_level’ parameter allows you to control the AI’s ‘depth of thought’ or internal reasoning phase.
Another development is the generation of generative user interfaces (UI); developers can generate interactive web UIs directly from prompts. Google has presented the following example:
Discontinuation of models at Gemini
The following models have already been discontinued:
- Gemini 2.0 Flash & Flash-Lite (since 1 June 2026)
- Gemini 3 Pro Preview (since 9 March 2026)
- Gemini 2.5 Flash Image Preview (since 15 January 2026)
- All Imagen models (since 24 June 2026)
- Gemini 1.0 and 1.5: completely discontinued; API requests return a 404 error
Planned discontinuation:
- Gemini 2.5 Pro, Flash and Flash-Lite: from 16 October 2026 at the earliest (successor: the 3.x series
Gemini 1.0 (Ultra/Pro/Nano, late 2023) and 1.5 laid the foundations for Google’s multimodal AI, but have been completely phased out since 2026. Gemini 2.0 (December 2024) introduced autonomous agent capabilities for the first time, but has since been completely replaced by Gemini 3.
How Can Google Gemini be used?
Gemini 3.1 Pro is available to developers as a preview via the Gemini API in Google AI Studio, Gemini CLI, Antigravity, Vertex AI, and Android Studio, for both end users, developers and enterprises, with a focus on multimodality, generation, automation, and personalization.
Google AI Pro (formerly Gemini Advanced) subscribers can use Gemini models with no usage limit. Non-paying users still have access to Flash and Pro variants, but with limited usage limits; as soon as the limit is reached, they automatically fall back to the next lowest model variant, usually Gemini 3 Flash or — if not available — Gemini 2.5 Flash.
Google is now also making Deep Research available free of charge in the current 2.5 Flash model.
On Google Android smartphones, Gemini replaces the Google Assistant as Standard AI assistant. In use are various Gemini Nano models, which work multimodally and interact via text, images, or speech. For iOS users, the Gemini app needs to be installed to gain access to Gemini models via Apple devices.
Gemini's deep integration with Google's ecosystem, including Gmail, Calendar, Keep and Maps, It also improves the user experience and makes it easier to provide information. Google explains this feature as follows: “Have Gemini pick the lasagna recipe from your Gmail account and ask the AI Assistant to add the ingredients to your Keep shopping list.”
Within Google Maps, users can, for example, ask about activities or locations directly in the app, and Gemini provides personalized recommendations — all in real time and without their own search. Gemini is also replacing the Google Assistant on Google TV and with a new function, Gemini can operate smart home devices in the lock screen so that users can easily control the lights, heating or cameras, for example, without unlocking their mobile phones.
Google Gemini or GPT?
Gemini 3.1 and GPT-5.1 are close competitors in 2026, albeit with complementary strengths.
When OpenAI was launched in November 2022 with ChatGPT When the GPT-3 model was launched, the hype was enormous and Google was waiting for it to answer. It wasn't until March 2023 that Google released Bard, the predecessor of Gemini, which initially stood out primarily due to incorrect or humorous answers. However, with the renaming and development to Google Gemini, the chatbot has made a significant leap in quality and is now considered a serious competitor. Gemini is growing aggressively (18-24% GenAI market share at the beginning of 2026), particularly through search, Android and workspace integration (~750M MAU), but lags behind ChatGPT (~1-1.3 B MAU, 60-70% market share).
Gemini particularly shines when it comes to multimodality and Google integration, whereas GPT-5 shines when it comes to adaptive reasoning and developer tooling. We have briefly summarized recommendations for use:
From a technical point of view, both systems are constantly catching up. Gemini is currently doing very well in benchmarks for multimodality (processing of text, image, audio, video). GPT-5, on the other hand, is a leader in the areas of logical thinking, complex reasoning and scientific applications. OpenAI also relies on highly specialized submodels and advanced API functions, while with Gemini, Google focuses more on seamless integration into the Google ecosystem and everyday applications, but also on creative features such as video creation (Veo).
Which model is the “better” choice therefore depends heavily on the application. Both are thus setting new standards for the practical use of AI.
In addition to these top companies, however, the other competing players for chatbot systems and large language models should not be forgotten, which are also advancing. For example, because some require less computing power. We offer a detailed Overview of 20 ChatGPT alternatives in another article.
Conclusion
Google Gemini has established itself as a versatile AI system that stands out in particular due to its multimodal strengths and integration into the Google ecosystem. It also shines with continuous additions to functions such as Gemini Live, Scheduled Actions or Veo. Gemini is thus increasingly positioning itself as a personal assistant who takes on tasks and supports creative processes.
OpenAI, on the other hand, is setting new standards in the area of logical thinking and complex reasoning with GPT-5. While Gemini is particularly impressive with an enormous context window, multimodal processing and practical functions, GPT-5 shows its strengths in analytical depth and linguistic precision. The choice of the appropriate model therefore depends heavily on the intended use:
- Gemini is particularly suitable for users who value everyday usability and creative experiments and may already make heavy use of Google services.
- GPT-5, on the other hand, remains the first choice for demanding analysis and research tasks.
One thing is clear: Both systems will set the standard in the AI landscape in 2026 and drive competition forward.
Despite their impressive functionalities, Google Gemini and GPT‑5 are only conditionally suitable for companies' customer communication. Control over content and tonality, as well as legal requirements, are limited. moinAI combines the power of modern language models with complete control over cost and communications, so that companies can develop chatbots that operate consistently and in line with the brand.
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