Contents
What?
This article introduces the Google Gemini ecosystem—a family of AI models from Google DeepMind—and explains what its key components are and what they do: Gemini Omni, Gemini Audio, Gemini Robotics, Gemini 3.5 Transcribe, and Gemini 3.7 Flash.
Why is this important?
Google is consistently expanding the Gemini ecosystem with new, specialized models, which are finding their way into a growing number of products – from search to Gboard to developer tools. Some of the features described here, like Gemini 3.5 Transcribe, have only been released in recent days, so it's worth knowing which features are already available and which are still in the testing phase.
Who is it for?
Those interested in Google's AI developments, marketers and content creators, developers working with Gemini models, and anyone who wants to understand the breadth of the Gemini ecosystem beyond just chatbots.
Background:
Google Gemini was initially associated primarily with a chatbot competing with ChatGPT, but over time it has evolved into a much broader ecosystem of specialized AI models. Instead of a single, universal solution, Google is now developing separate models for specific areas—multimedia, audio, robotics, or programming—that can also collaborate on more complex tasks. This strategy differs from the approach of some competitors, who focus on a single, universal model, and illustrates the direction in which the development of large AI ecosystems may be heading in the coming years.
Google has been investing in artificial intelligence for years, and one of its most important projects is Google Gemini—a family of AI models developed by Google DeepMind. Gemini integrates various intelligent features across Google products, from Search to Gmail and Docs to mobile apps, offering a wide range of applications in everyday life and work. But what exactly is Google Gemini, which models it comprises, and how does it all work? We explain it step by step.
What is the Gemini ecosystem and what models are included in it?
ecosystem is not a single model, but a whole family of AI solutions created by Google DeepMind, each addressing a different application area. It includes:
- Gemini Omni — support for creating multimedia and interactive content,
- Gemini Audio – audio processing and transcription,
- Gemini Robotics — models supporting the interaction of robots with the environment,
- Gemini 3.5 Transcribe - speech to text,
- Gemini 3.7 Flash - Helping developers code and create AI agents.
Each of these models handles a different piece of the larger puzzle—from content creation and audio processing to robotics and programming—making Gemini one of the most comprehensive AI ecosystems on the market today. The table below summarizes this:
| Model | Main use | Availability |
|---|---|---|
| Gemini Omni | Creating interactive multimedia content | Used together with other models (e.g. 3.7 Flash) |
| Gemini Audio | Audio processing and transcription | Expanded, some functions publicly available |
| Gemini Robotics | Robot perception and action in the physical world | Limited - Trusted Test Partners |
| Gemini 3.5 Transcribe | Real-time speech-to-text | Public Test (macOS, Gboard, AI Studio) |
| Gemini 3.7 Flash | Rapid Coding and Creation of AI Agents | Publicly available via API and Google AI Studio |
What is Gemini Omni and how does it support multimedia content creation?
Gemini Omni is a model that supports the creation of interactive and multimedia content —from dynamic visual elements on websites to engaging components in applications. In practice, it is often used in conjunction with other Gemini models (e.g., Gemini 3.7 Flash), which separate tasks: one model is responsible for the overall logic and structure, while Gemini Omni generates fluid, interactive multimedia elements in real time.
In practice, it might look something like this: the Gemini 3.7 Flash model plans the structure of an interactive landing page (e.g., a landing page for a marketing campaign), while Gemini Omni handles generating smooth visual effects and scrolling animations (so-called parallax), which would be difficult to manually code in a short time. This illustrates the direction in which the entire Gemini ecosystem is evolving— instead of a single universal model, several specialized solutions work together to achieve a single end result.
For content creators and marketers, this means potentially reducing the time it takes to prepare visuals – although, as with any AI tool supporting content production, it’s always worth verifying the final result for brand consistency, just like when working with other AI tools.
What is Gemini Audio and how does it process audio in real time?
Gemini Audio is the area of Gemini models responsible for audio processing, including real-time speech transcription. One of its components is the aforementioned Gemini 3.5 Transcribe, which can transcribe audio both live (from ultra-low-latency audio streams) and from recorded audio, with speaker recognition and time stamping.
Practical applications of Gemini Audio include:
- customer service – automatic transcription of telephone calls for further analysis,
- meetings and notes – convert meeting recordings into structured text,
- Video Subtitles – Quickly generate subtitles for video content in multiple languages,
- Voice assistants – support for real-time voice interactions in applications and devices.
This solution is therefore of practical importance both for large companies working with large amounts of voice recordings and for smaller teams that want to save time on manually transcribing conversations or meetings.
What is Gemini Robotics and how does it support interaction with tools in robotics?
Gemini Robotics is a family of AI models that combine perception, reasoning, and action to help robots better understand their environment and perform complex physical tasks —from precisely grasping objects to planning multi-step actions. In practice, this family is divided into several variants: a model responsible for the actual control of the robot's movement (translating image and voice commands into specific motor commands), a model responsible for "high-level" reasoning (task planning, coordinating several robots simultaneously), and a version that operates locally, without an internet connection—important in environments where a stable connection is not guaranteed.
It's worth noting, however, that access to these models is currently limited —they are primarily used by trusted Google DeepMind testing partners, such as Boston Dynamics and Agility Robotics, rather than a broad user base or developer base. Test results published by DeepMind also show that the robots' performance strongly depends on the specific task—some tasks (e.g., picking up items from a shelf) perform significantly better than others (e.g., precise manual tasks like tying a bag), which indicates that this is still an early-stage technology, not a ready-made, universal solution.
Still, the direction of development is clear: Gemini Robotics is showing how language models can go beyond the world of text and images, interacting with the physical world—which could have long-term implications for automation in industry and logistics.
What is Gemini 3.5 Transcribe and how does it convert speech to text?
Gemini 3.5 Transcribe is one of Google's newest speech-to-text models, designed with naturalness and precision in mind, and was launched just a few days ago. Its key features include:
- removing filler words (e.g. "uh", "so") and automatic text formatting,
- recognition of multiple speakers in a recording with time stamps,
- support for over 85 languages, including various accents and dialects,
- voice text editing – the user can correct the transcription by saying subsequent commands,
- autocorrect recognition in speech - if someone says "let's meet on Tuesday, no, Wednesday", the model understands that it was Wednesday and saves the text accordingly.
Gemini 3.5 Transcribe works in two modes: real-time transcription (streaming, with very low latency—for applications like live captions or voice assistants) and processing of existing recordings (with full speaker identification). It's already available in Gemini for macOS, the Gboard keyboard (Rambler feature), and Google AI Studio for developers, with integration with Chrome planned. This demonstrates that speech transcription is no longer a niche function but is becoming a standard element of everyday text processing.
What is Gemini 3.7 Flash and how does it support advanced coding and agent creation?
Gemini 3.7 Flash is a Google model optimized for speed and for working with AI agents —systems that independently perform multi-step tasks, rather than simply responding to single commands. It's useful for generating interactive websites, orchestrating multiple collaborating "sub-agents," and transforming static documents (e.g., PDF reports) into interactive, visual summaries with charts.
Some specific use cases that Google itself shows include:
- transforming a simple text description into a playable, interactive 3D game,
- generating ready-made, interactive landing pages based on a single command,
- support in training robotic models by accelerating the learning loop,
- turning static annual reports into interactive, visual “data stories” with live charts.
For programmers, this means a tool that combines speed with real usefulness in more complex, agent-based programming tasks – it not only generates individual pieces of code, but can also coordinate entire processes composed of several steps.
Is Google Gemini worth using?
Google Gemini is one of the most extensive AI ecosystems on the market today . Instead of a single, universal model, Google focuses on several specialized solutions (multimedia content, audio, robotics, transcription, coding) that can be combined depending on needs. This approach has its advantages: users or developers can choose a model tailored precisely to the task, rather than a compromised, one-size-fits-all tool.
It's worth remembering, however, that some of these models—like Gemini Robotics—are still in the limited-access phase, while others, like Gemini 3.5 Transcribe, have only just become widely available. Consciously using Google Gemini means keeping track of which features are already publicly available and which are still being developed, as well as examining how companies are adapting their content and processes to accommodate the growing role of AI in search and customer communication—a topic we discuss in more detail in our article on GEO (Generative Engine Optimization) and its importance in e-commerce.
