Google's AI Name: Gemini - Specs, Features & Updates for 2025

Introducing Gemini: Google's Flagship AI

Google's main AI is called Gemini. It's their most powerful and capable AI model. Gemini isn't just one thing; it's a family of AI models. These models come in different sizes for different tasks.

The Gemini family powers many Google products and developer tools. It's Google's answer to the growing world of AI and marks a new chapter for the company in 2025.

Key features of Gemini include:

• It's Google's main AI.
• It can understand text, images, and more.
• It's a base for other AI tools.
• It's built into many Google apps.

The Evolution from Bard to Gemini

Getting to Gemini involved a big name change. Google's first conversational AI was called Bard. At first, Bard used a simpler AI model. Later, it was updated with early versions of Gemini.

In early 2025, Google simplified its AI products. Bard was officially renamed Gemini. This change made Google's AI brand clearer and showed off the powerful tech behind it. The new name shows that the Gemini models are now running the show.

This change had several benefits:

• Unified Branding: All of Google's AI tools for users are now called Gemini.
• Better Performance: The AI model got a big upgrade, giving users access to the powerful Ultra 1.0 version.
• Clearer Strategy: This move shows that Gemini is the center of Google's AI plans [source: https://blog.google/products/ai/bard-gemini-google-ai-update/].

So, if you're wondering what Google's AI is called, the answer is Gemini. It's more than just a chatbot; it's a complete AI system.

The Meaning and Significance Behind the Name

The name "Gemini" for Google's AI is full of meaning. It comes from the Latin word for "twins" and also refers to the famous Gemini constellation. This name reflects the main idea behind Google's most advanced AI.

At its core, Gemini represents the idea of being versatile. This fits its new ability to work with many types of information [source: https://blog.google/technology/ai/google-gemini-ai-model-deepmind/]. Gemini can easily understand and use different kinds of data, like text, code, images, audio, and video. This "twin" aspect highlights its skill in handling various forms of information.

The name also suggests a blend of different strengths. It stands for a powerful mix of what AI can do. Google's goal for Gemini is clear: to create one adaptable AI that can handle many complex jobs. This is a big step up from older AI systems that could only do one thing.

The name also has a historical link to big human achievements. NASA's Project Gemini was a key part of the journey to the moon, connecting the earlier Mercury missions with the Apollo missions. In the same way, Google's Gemini is meant to close the gap between what AI can do now and what it will do next, pushing it into a new, more useful era.

Google's Strategic Vision for the Gemini Era

The launch of Gemini shows a major new direction for Google. The company wants to create the world's best and most capable AI. This plan focuses on building a single AI that can do almost anything. Gemini is made to be both flexible and efficient.

A key part of this strategy is building a strong core model. Gemini was designed from the start to handle many data types. It has advanced skills in reasoning and understanding, which lets it pick up on subtle details. This means it can give smart, relevant answers in many different situations [source: https://deepmind.google/discover/blog/introducing-gemini-our-new-state-of-the-art-model/]. These abilities are vital for the future of AI.

Google also plans to put Gemini into everything it makes. It will be used to power products like Search, Google Assistant, Chrome, and Android, and will also improve Workspace apps. By adding Gemini everywhere, Google wants to make AI features easier for everyone to use and to improve people's daily experiences with its products throughout 2025.

Google's strategy also includes developing AI responsibly. Safety and ethics are very important. The company is focused on building AI that is helpful, safe, and fair for everyone. This means it will be tested thoroughly and improved over time. The main goal is to release useful AI tools for people all over the world.

With AI changing so quickly, Google is making Gemini its main focus. It is the company's answer to new AI from competitors. Gemini shows that Google is serious about being a leader in artificial intelligence. It will be the power behind many new inventions in the coming years.

Gemini Models Explained: Ultra, Pro, and Nano

Google's Gemini AI is designed in three tiers. This design ensures it performs well for many different uses. Google offers three models: Ultra, Pro, and Nano. Each model is built for different tasks and power needs.

This layered approach is very efficient. Developers and users can choose the best model for what they need to do. This flexible system shows Google's smart approach to AI.

Model Name	Key Characteristics	Primary Use Cases
Gemini Ultra	The largest and most powerful Gemini model, built for highly complex tasks. Ultra is excellent at advanced reasoning and understanding different types of information. It's the top choice for demanding computing needs [source: https://deepmind.google/technologies/gemini/].	Large-scale enterprise applications, complex scientific research, advanced coding projects, sophisticated chatbots, and demanding AI-driven services.
Gemini Pro	A balanced model that is both powerful and efficient. It's versatile and can handle a wide range of tasks. Gemini Pro is the engine behind many Google products, including the main Gemini chatbot [source: https://blog.google/technology/ai/google-gemini-ai/].	General-purpose AI applications, conversational AI, content generation, data analysis, and integrating AI into various Google services in 2025.
Gemini Nano	The smallest and most efficient model. Nano is made to run directly on devices like smartphones. It works well without using a lot of power, making it perfect for mobile use. This allows for direct integration into smartphones and other edge devices.	On-device AI features for smartphones (e.g., summarization, smart replies), offline AI capabilities, enhancing user experience without cloud reliance, and privacy-sensitive local processing.

Core Capabilities: Multimodality, Reasoning, and Coding

Gemini has three standout features. These features allow it to solve complex problems in smart and flexible ways. Google built Gemini from the start to be multimodal. Its powerful reasoning and coding skills also make it a very useful tool.

• Multimodality: Gemini is multimodal, which means it can naturally understand and work with different kinds of information at once. This includes text, images, audio, and video. This allows Gemini to understand real-world situations more accurately. For example, it can watch a video, understand what's being said, and see the objects in it all at the same time [source: https://blog.google/technology/ai/google-gemini-ai-developers-experience/]. This deep understanding is more like how humans think.
• Advanced Reasoning: This AI model shows advanced reasoning skills. It can understand complex information, find patterns, and make logical connections. Gemini is also great at solving problems, even tricky ones. Its ability to think abstractly and handle difficult tasks is impressive. It does more than just match patterns.
• Powerful Coding: Gemini is excellent at coding and software development. It can write high-quality code in many different programming languages. Developers can use it to fix bugs or explain complicated pieces of code. Because it knows many languages, it's a helpful assistant for programmers everywhere [source: https://www.infoq.com/news/2023/12/google-gemini-code-assistant/]. This helps developers be much more productive.

Integration with Google Assistant and Workspace Apps

A key strength of Gemini is how well it works with other Google products. This improves the user experience a lot and boosts productivity everywhere it's used. In 2025, Gemini will change how you use Google Assistant and Workspace apps.

• Enhancing Google Assistant: Gemini's advanced skills are built directly into Google Assistant. This makes conversations with the Assistant feel more natural and intelligent. Users can expect better understanding of context and more helpful, proactive suggestions. For example, the Assistant can now manage longer, more complex conversations and personal requests. This makes using it every day feel smoother and more natural [source: https://blog.google/products/assistant/google-assistant-gemini-generative-ai/].
• Powering Workspace Applications: Gemini greatly improves how Google Workspace apps work. It works with tools like Gmail, Docs, Sheets, and Slides. This helps streamline work and automate repetitive tasks.
  • Gmail: Gemini can help draft emails, summarize long threads, and suggest quick replies. This saves a lot of time.
  • Docs: It assists in generating content, proofreading documents, and refining writing styles. Users can focus on ideas, not formatting.
  • Sheets: Gemini can analyze data, create formulas, and generate insights from complex datasets. Data interpretation becomes faster and more accessible.
  • Slides: It aids in creating compelling presentations, suggesting layouts, and generating relevant content for slides. Professional presentations are now easier to produce.

  Gemini acts like a smart co-pilot, making both individuals and teams more productive across all Workspace apps.

A Head-to-Head Comparison: Gemini vs. GPT-4o

The world of artificial intelligence is always changing. In 2025, two of the biggest names are Google's Gemini and OpenAI's GPT-4o. Both are top-tier large language models (LLMs) with advanced skills for many different tasks. But because they are built and trained differently, they have their own unique strengths.

Google's Gemini, especially the Ultra 1.5 version, is built to handle many data types. It's great at processing text, images, audio, and video. It also has a very large context window, allowing it to work with a lot of information at once. On the other hand, OpenAI's latest model, GPT-4o, also has strong multimodal skills. It's designed to be fast and efficient, which makes it perfect for real-time conversations and apps. Let's break down their main differences:

Feature	Google Gemini (Ultra 1.5)	OpenAI GPT-4o
Multimodality	Native multimodal architecture. Processes text, image, audio, video inputs seamlessly.	End-to-end multimodal. Processes text, audio, image as input/output.
Context Window	Up to 1 million tokens (for advanced users) [source: https://deepmind.google/technologies/gemini/]. This allows for processing extensive documents or long videos.	128k tokens. Sufficient for many complex tasks but smaller than Gemini's top tier.
Reasoning	Strong logical reasoning, complex problem-solving. Excels in scientific and mathematical tasks.	Highly capable across general reasoning tasks. Strong in common sense and nuanced understanding.
Coding	Proficient in generating, debugging, and explaining code across many languages.	Excellent coding capabilities. Strong in various programming languages and software development tasks.
Speed/Latency	Optimized for complex, long-context tasks. Processing time can vary with context length.	Designed for high speed and low latency. Ideal for real-time interactions and rapid responses.
Integration	Deep integration with Google products (Workspace, Android).	Integration via API, powers various third-party applications and Microsoft Copilot.

Performance Benchmarks and Real-World Use Cases

To truly compare AI models, we need to look beyond their features. Performance benchmarks offer a standard way to measure them, while real-world examples show how they are actually used. Both Gemini and GPT-4o get top scores on many key academic tests. These include:

• MMLU (Massive Multitask Language Understanding): Tests knowledge in 57 subjects. Both models score very high, often better than human experts [source: https://arxiv.org/abs/2402.04944].
• GSM8K: Tests math skills. Both are good at solving hard word problems.
• HumanEval: Checks coding skills. Both are skilled at writing code that works correctly.
• Vision Benchmarks: Tests like VQA and Captioning. Both are great at understanding and describing images.

In the real world, their strengths often match how they were designed:

• Gemini's Strengths:
  • Long-Form Content Analysis: Summarizing entire books or analyzing hours of video footage.
  • Scientific Research: Assisting with complex data interpretation and hypothesis generation.
  • Advanced Coding Projects: Generating extensive codebases or refactoring large projects.
  • Multimodal Tutoring: Explaining concepts using text, diagrams, and spoken language.
• GPT-4o's Strengths:
  • Real-time Customer Support: Providing instant, accurate responses across channels.
  • Interactive Storytelling/Gaming: Generating dynamic narratives and character dialogue.
  • Voice Assistants: Powering highly natural and responsive conversational agents.
  • Creative Content Generation: Quickly producing diverse text, image, and audio outputs for marketing or media.

Both models are always improving. The 2025 versions are expected to be even smarter and faster. The best choice really depends on what you need for a specific task—whether it's a large context, high speed, or the ability to use different data types.

How Gemini Stacks Up Against Claude and Microsoft Copilot

While Gemini and GPT-4o get most of the attention, there are other strong competitors, like Anthropic's Claude and Microsoft Copilot. Let's see how Gemini compares to them for a fuller view of the market.

Gemini vs. Claude (e.g., Claude 3 Opus):

Anthropic's Claude models, particularly Claude 3 Opus, are famous for focusing on AI safety. This makes them a popular choice for tasks where safety and fairness are very important. Claude also has a large context window, making it great for tasks like reviewing legal documents or analyzing long reports [source: https://www.anthropic.com/news/claude-3].

• Ethical Alignment: Claude is carefully trained to avoid generating harmful responses.
• Long Context: Competitive with Gemini in handling very large inputs for text-based tasks.
• Reasoning: Claude 3 Opus is also great at reasoning, especially when understanding subtle details in text.
• Multimodality: While Claude 3 can understand images, it is not as fully multimodal as Gemini or GPT-4o. Its main strength is text.

Gemini vs. Microsoft Copilot:

Microsoft Copilot is different. It's an AI assistant built into Microsoft 365 services. Copilot mainly uses OpenAI's GPT models (like GPT-4o) along with Microsoft's own technology. Its biggest advantage is that it's deeply connected to the Microsoft ecosystem, helping people be more productive in apps like Office, Windows, and Edge [source: https://www.microsoft.com/en-us/microsoft-copilot].

• Ecosystem Integration: This is Copilot's key advantage. It works smoothly inside Word, Excel, PowerPoint, Outlook, and Teams.
• User Interface: Designed as an intelligent assistant, making AI accessible for everyday tasks.
• Underlying Models: Uses the power of OpenAI's top models.
• Focus: Copilot's goal is to improve productivity inside existing software. In contrast, Gemini is a foundational model that developers can access directly through an API or a chat app.

To sum up, Gemini is a core multimodal model with powerful processing ability and a huge context window. Claude is a strong and safe alternative, especially for text-based tasks. Finally, Microsoft Copilot is an application that uses models like GPT-4o to bring AI help directly into the programs people use every day, making work easier in the Microsoft ecosystem.

Is Google's AI called Bard or Gemini?

Google's AI is now called Gemini. Previously, it was known as Bard. Google officially renamed Bard to Gemini in early 2024. This change was made to reflect an upgrade to the more powerful Gemini technology that runs it [source: https://blog.google/products/bard/bard-gemini-advanced-sundar-pichai-update/].

This new name shows Google is focusing on a single brand for its AI. It also highlights the advanced abilities of the Gemini models.

What was the old name for Google's AI?

The old name for Google's AI chatbot was Bard. It was first launched in early 2023. It was renamed Gemini as Google continued to improve its AI technology [source: https://blog.google/products/bard/bard-gemini-advanced-sundar-pichai-update/]. The change aligned the chatbot with Google's more powerful Gemini models.

Is Google Gemini free to use?

Yes, there is a free version of Google Gemini. You can use the standard version for everyday conversations and tasks at no cost.

Google also has a paid subscription called Gemini Advanced. This version gives you access to Google's most powerful AI model, Ultra 1.0, and usually has more features [source: https://gemini.google.com/upgrade]. Gemini Advanced is available through the Google One AI Premium plan for a monthly fee and works with other Google services.

What is the name of the Google AI chatbot?

The Google AI chatbot is named Gemini. It is Google's main conversational AI, designed to understand and create human-like text, code, and more [source: https://gemini.google.com/].

Gemini is a powerful AI that can work with different kinds of information, not just text. For example, it can process and understand images, audio, and video. It is also built into other Google products, like Google Assistant and Google Workspace apps.