What is Gemini 2.5? A simple explanation of Google's latest AI

The road to becoming an AI creator | Article introduction: What's so great about Google's latest AI "Gemini 2.5"? Easy-to-understand explanation for beginners! We'll reveal the secrets of the "thinking AI" that will change the future! #Gemini25 #GoogleAI #AIExplanation

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[For beginners] What is Google's latest AI "Gemini 2.5"? A thorough explanation of the secrets of this super-intelligent "thinking AI"!

Hello, I'm John, an AI technology blogger! Recently, Google announced a new AI calledGemini 2.5" has become a hot topic. "It seems amazing, but what's so great about it?" "Does it have anything to do with us?" For those of you who have such questions, today I would like to explain Gemini 2.5 in an easy-to-understand way, using as few technical terms as possible!

What is Gemini 2.5? Let's get the basics down!

Gemini 2.5 is the latest family of AI models developed by Google.reasoning modelThis is the revolutionary feature of AI, which does not simply store and output information, but rather "thinks" like a human before giving an answer.

Previous AIs were also smart, but Gemini 2.5 is good at solving more complex problems and creating multi-stage plans. It can truly be called the "next generation AI."

What problem does Gemini 2.5 aim to solve?

In today's society, information is exploding. It can be difficult to find, understand, and use the information you really need. Gemini 2.5 was developed to solve the following problems:

More advanced information processing: Large amounts of text, images, audio, video, and even computer program code, all kinds of information (which we callMultimodal (capable of handling multiple types of information, such as text, images, and audio)The goal is to improve the ability to simultaneously understand and process multiple types of information (called ``multiple types'').
Automate complex tasks: Enabling AI to support more complex tasks and creative work that previously required human judgment.
More natural dialogue: Making communication between humans and AI smoother and more intuitive.

Unique Features of Gemini 2.5

The biggest feature of Gemini 2.5 is, of course,thinking process" This allows the AI to have a moment to think before generating a response, which can result in more accurate, contextual, and high-quality output.

Other unique features include:

Model family expansion: There are several models available to choose from depending on your needs and budget.Gemini 2.5 Pro", balanced "Gemini 2.5 Flash" and the fastest and most cost-effective "Gemini 2.5 Flash-Lite"And so on.
Flexible "thinking" control: Through APIs, developers may be able to tune how the model "thinks," allowing them to tailor its performance to the nature of the task at hand.
Native multimodal support: It was designed from the beginning to be able to handle multiple types of information, including text, images, audio, video, and code, so its strength is that it can easily handle complex tasks that combine these types of information.

Gemini 2.5 Model Lineup and Availability: Which is Right for You?

Gemini 2.5 is not a single model, but rather comes in several variations. Learn about the features of each one so that you can choose the one that best suits your needs if you have the opportunity to use them in development or other situations.

Gemini 2.5 Pro

"Gemini 2.5 Pro" is currently considered the most high-performance model. Google itself has positioned it as "our most advanced reasoning Gemini model" and "Our most capable model," and it can be said to be a flagship model with "diamond"-class capabilities. It is designed to handle the most difficult tasks, such as highly complex reasoning, generating advanced programming code, and understanding specialized content.

Specialties: Complex problem solving, long-form text understanding and generation, domain-specific analysis, advanced coding assistance, scientific tasks, and more.
Availability: It is now generally available (GA) through Vertex AI (Google Cloud's machine learning platform), Gemini API, and Google AI Studio (a developer tool for experimenting with AI models).

Gemini 2.5 Flash

"Gemini 2.5 Flash" is a model with an excellent balance of speed and performance. It meets the needs of those who don't need the ultra-high performance of the "Pro" but want to perform everyday tasks quickly. Google describes it as "Our best model in terms of price-performance," and it has the image of working briskly like the "Spark."

Specialties: Tasks that require a fast response, such as summarization, chatbots, classification, everyday text generation, etc. Optimized for cost-effectiveness and low latency.
Availability: This is also generally available on Vertex AI, Gemini API, and Google AI Studio. Recently, the pricing structure has changed, with the price per million input tokens (units of data processed by AI) increasing from $100 to $0.15, but the price per million output tokens decreasing from $0.30 to $100, and the price difference between the presence and absence of thinking functions has disappeared.
point: It is ideal for situations where you want both fast response and cost-effectiveness.

Gemini 2.5 Flash-Lite

The new preview version is "Gemini 2.5 Flash-Lite" As Google describes it, this is the most cost-efficient and fastest 2.5 model yet in the Gemini 2.5 family. It is the most cost-efficient and low-latency model. It is particularly effective when you want to process large amounts of tasks efficiently.

Specialties: High-throughput tasks where throughput (amount of processing per unit time) is important, such as large-volume data classification, large-scale summarization tasks, and chat responses.
Characteristic: By default, the "thinking" function is off, but it can be turned on with API parameters (thinking controls). It is optimized with low cost and low latency as the top priority. It is positioned as an upgrade from Gemini 1.5 Flash and 2.0 Flash models.
Availability: It is currently available as a preview.

These models will enable developers to choose the AI that best suits their project requirements (complexity, speed, cost), and consumers will benefit from these AI models through Google services and third-party applications.

Gemini 2.5's technical structure: How does AI "think"?

Well, the question you're probably wondering is, "How does Gemini 2.5 "think" like a human?" To fully understand this requires specialized knowledge, but here we'll explain it simply so that even beginners can get an idea of what it is.

The core technology of Gemini 2.5 isLarge Language Model (LLM)" This is an AI that has acquired the ability to understand human language, generate sentences, and answer questions by studying vast amounts of text data and code.

Gemini 2.5 is especiallyreasoning model"Or"thinking modelThe reason it is called " is because it has "Thinking process" This is because it incorporates a mechanism that can be said to be "enhanced performance and improved accuracy." According to Google, this thought process brings about "enhanced performance and improved accuracy." This is thought to be because, rather than immediately generating a response to a question or instruction, it takes steps such as exploring multiple possibilities internally, examining related information from multiple angles, and breaking down the problem step by step.

Image of the specific mechanism:

Input Understanding: First, it deeply understands the questions and instructions (called prompts) from the user. Gemini's strength is that it can simultaneously understand not only text, but also images, audio, video, and code (Native MultimodalityGoogle states that "Gemini is built from the ground up to be multimodal."
Internal thoughts and plans: Next, instead of coming up with an answer right away, think internally about "how can we come up with the best answer?"
- If the question is complex, break it down into smaller steps (multi-step planning abilities).
- Check multiple sources to see if there are any contradictions.
- Generate several possible responses and evaluate which one is most appropriate.
A new feature of Gemini 2.5 is that developers may be able to adjust this "thinking time" and "thinking depth" depending on the task.Controlling your thought budget).
Response generation: After careful consideration, it outputs what it determines to be the most appropriate answer in natural prose, code, or some other format.

Thanks to this "thinking" step, Gemini 2.5 is expected to outperform previous models in the following ways:

Higher accuracy: Because you're thinking things through instead of just responding on impulse, you're less likely to make mistakes.
Dealing with complex instructions: It can also accurately follow multi-step instructions such as "Do A, then B, and if C, then do D."
Increased creativity: It will not only enable you to search for information, but also help you come up with new ideas and write more creatively.

According to Google, this "thought process" significantly improves the machine's ability to solve complex mathematical problems, gain deeper insights from long documents, and perform advanced programming tasks, among other things.

The development team and community: Who is building it and how is it being used?

Development team: Google DeepMind's technical capabilities

Gemini 2.5 is a joint venture between Google and the AI research and development division,Google DeepMind" is the main developer of Gemini. Google DeepMind is a cutting-edge AI research organization that has become world famous for its Go AI "AlphaGo". High-performance AI like Gemini is born from the results of many years of AI research, the vast amount of data that Google possesses, and powerful computing resources (computer power).

Google has set a mission to make AI "useful for everyone," and Gemini is being developed as part of that mission. The company has also announced that it is focusing on ensuring reliability and security.

Community and Ecosystem

Gemini 2.5 is available through the developer platform.

Vertex AI: Google Cloud's integrated machine learning platform. Used by companies to incorporate Gemini into their own services. "Gemini 2.5 Pro" and "Gemini 2.5 Flash" are generally available here.
Gemini API: An interface for developers to use Gemini's features from their own applications and services. Pro and Flash versions are also generally available.
Google AI Studio: A tool that allows developers to easily experiment with Gemini models and create prototypes in a browser. Also available in Pro and Flash.

Through these tools, developers around the world have begun to develop new applications and services using Gemini 2.5. The formation of an active developer community is expected to further accelerate the evolution and adoption of AI technology.

Google regularly publishes the latest information on its blog and developer documentation, and continues to improve its models while collecting feedback. For example, on June 2025, 6, there were important updates, such as the general availability of Gemini 17 Pro and Flash, the announcement of a preview version of Flash-Lite, and the revision of pricing for the Flash model. This can be seen as part of Google's proactive disclosure and support of the developer community.

Gemini 2.5 use cases and future prospects: How will our lives change?

Gemini 2.5, a "thinking AI," is expected to play an active role in various aspects of our work and life. Let's take a look at some specific examples of its use and its future potential.

Specific examples of use

Advanced coding assistance: It helps programmers write complex code, find bugs, and helps them learn new programming languages. Gemini 2.5 Pro is said to be particularly good in this area. "Advanced code generation" is one of its main features.
Data analysis and insight extraction: It analyzes large volumes of documents, reports, customer data, etc., and presents key trends and insights in a human-friendly format, enabling faster and better business decisions. Models like Flash-Lite are well suited for "classification or summarization at scale."
Creative content creation: It supports creative work, such as coming up with ideas for novels and scripts, creating catchy slogans, and even supporting music and image generation. Because it supports multimodal content creation, it is expected to combine not only text but also images and audio.
Use in education: It is expected to play a role similar to that of an "AI private tutor," providing personalized learning materials and carefully answering questions based on each individual's learning progress and level of understanding.
Medical applications: By analyzing vast amounts of medical papers and clinical data, it has the potential to contribute to diagnostic support and the discovery of new treatments.
A smarter search engine: Rather than simply providing information that matches keywords, it may be possible to gain a deeper understanding of user intent and provide the answers and solutions they are truly looking for.
Multilingual translation and communication support: More natural and accurate translation facilitates communication across language barriers.
Speech dialogue system: Gemini 2.5 also has advanced speech understanding and generation capabilities (Google announced "Advanced audio dialog and generation with Gemini 2.5"), which is expected to lead to more natural, human-like voice assistants and conversational AI.

Future outlook

The evolution of "thinking AI" such as Gemini 2.5 has the potential to bring about major changes in our society.

Productivity Boost: Various tasks will be automated and made more efficient, allowing humans to focus on more creative, higher value-added work.
Introducing new services: AI may give rise to innovative services and entertainment that were previously impossible.
Accelerating science and technology: AI has the potential to accelerate advances in science and technology by helping to solve complex scientific problems and make new discoveries.
The rise of personalized experiences: Services tailored to the needs of each individual will become available in all fields, including education, medical care, and entertainment.

Of course, the evolution of AI brings with it ethical challenges and the need for social consensus, but technologies like Gemini 2.5 have great potential to make our future richer and more convenient.

Comparison with the competition: What makes Gemini 2.5 different?

In the world of AI, many high-performance models have been developed, including those by Google, such as OpenAI's "GPT series" and Anthropic's "Claude series." So, what are the strengths of Gemini 2.5 among them?

Key strengths of Gemini 2.5 highlighted by Google include:

Advanced reasoning abilities: In particular"Gemini 2.5 Pro" is said to be "our most advanced reasoning Gemini model" and is said to show extremely high performance in tasks that require complex problem solving and logical thinking. Google announced that it has achieved the highest scores in many benchmarks (performance evaluation tests), and Reddit user comments include "Gemini 2.5 Pro is the current 'state of the art' large language model...getting the highest scores on several benchmarks designed to test for 'reasoning'."
Native Multimodality: Its main feature is that it is designed from the start to handle a wide variety of information, including text, images, audio, video, and code, in an integrated manner. This allows it to flexibly handle complex tasks that combine multiple types of information. For example, it can understand and summarize the content of a video, answer questions about an image, and generate code through voice instructions.
Efficiency and Scalability: "Gemini 2.5 Flash"Or"Flash-LiteModels such as Flash-Lite are optimized to achieve high efficiency and processing speed for specific tasks. Flash-Lite in particular is said to be the most cost-efficient reasoning model yet, and aims to perform large-scale processing at low cost (suitable for latency-sensitive, high-volume tasks), promoting the use of AI in a wide range of applications.
Integration with Google Ecosystem: Integration with a wide range of Google services and platforms, such as Google Search, Google Workspace (Gmail, Docs, etc.), and Google Cloud, can provide a seamless experience and a powerful development environment. It is also listed as a support model for Firebase AI Logic.
Introducing and controlling the "thought process": By having a step of "thinking" internally before responding, we aim to produce more reliable and contextual output. The fact that developers can control the degree of this "thinking" via API ("thinking controls") may be a unique approach not found in other models.

Of course, competing AI models are also evolving day by day, and each has its own areas of expertise and characteristics. For example, the GPT series has been highly praised for its natural conversational abilities and creativity, while the Claude series is said to have strengths in its ability to process long texts and ethical considerations.

Ultimately, there is no single best AI model, but rather it is important to choose the best model for your application and purpose. Gemini 2.5 will be a very attractive option for users and developers who value inference capabilities, multimodality, and cost-effectiveness depending on the task.

Risks and Cautions: What you need to know when using AI

Powerful AI like Gemini 2.5 has a lot of potential, but there are also caveats and potential risks to its use.

Accuracy of Information (Hallucination): AI can sometimes generate plausible false information (which isHallucinationGemini 2.5 tries to reduce this by "thinking," but it cannot prevent it completely. It is important not to accept information generated by AI at face value, but to make it a habit to verify it with multiple sources of information (fact-check) before using it for important decisions.
Bias issues: AI can reflect the biases contained in the training data. This can lead to unfair judgments against certain groups or the generation of discriminatory content. Developers are paying attention to this issue, but it is also important for users to have a critical perspective.
Potential Exploits: There is also a risk that advanced AI technology could be used for malicious purposes, such as creating fake news, committing fraud, and conducting cyber attacks.
Transparency Challenges: There are cases where humans cannot fully understand how an AI reaches a conclusion.Black box problemRecently, media outlets such as VentureBeat have reported that Google's recent decision to hide the raw reasoning tokens of its flagship model, Gemini 2.5 Pro, has sparked backlash from developers. This could raise concerns about AI transparency and control for developers who want to analyze and debug AI behavior in detail.
Employment Changes: As automation using AI advances, some jobs may be replaced by AI, and the content of jobs may change. Society as a whole will need to adapt to acquiring new skills and changing work styles.
Over-reliance: There are also concerns that relying too much on AI may diminish our own ability to think and make decisions. AI is nothing more than a tool, and it is important to use it wisely.
Regulatory Developments: With the rapid development of AI technology, discussions on legal regulations are underway in various countries. It is necessary to keep in mind that new rules on how AI should be used may be established in the future.

Understanding these risks and striving to use AI responsibly is important for both us as users and for society as a whole. Google itself has set forth the principles of "Responsible AI" and is working to ensure safety and fairness, but each and every user also needs to be aware of this.

Expert opinions and analyses (excerpts)

Many AI experts and technology analysts have released various opinions and analyses regarding Gemini 2.5. Here are some general opinions. (We do not endorse the opinions of any particular individual or media.)

Expectations for reasoning ability: Many experts are paying attention to the advanced reasoning capabilities that Gemini 2.5 Pro is said to have demonstrated. VentureBeat reports that "Gemini 2.5 Pro, positioned as Google's most capable model, excels at complex reasoning, advanced code generation, and multimodal understanding." In addition, OpenRouter.ai describes it as "Google's state-of-the-art AI model designed for advanced reasoning, coding, mathematics, and scientific tasks."
Possibilities of "thinking models": The approach of AI "thinking" before responding is evaluated as having the potential to improve AI reliability and its ability to handle more complex tasks. The "Google Developers Blog" explains that "Gemini 2.5 models are thinking models, capable of reasoning through their thoughts before responding, resulting in enhanced performance and improved accuracy."
Significance of the model family: Some people appreciate that providing models with different characteristics, such as Gemini 2.5 Pro, Flash, and Flash-Lite, makes it easier for developers to meet a variety of needs. An article in "InfoWorld" suggests the advantage of using these models depending on the task. In particular, Google states that Flash-Lite is "great for high throughput tasks such as classification or summarization at scale."
Increasing competition and its impact on the market: It is believed that Google's active rollout of the Gemini 2.5 family will further intensify competition with other AI development companies such as OpenAI and Anthropic, accelerating the evolution of AI technology as a whole. VentureBeat reports that Google has "launched production-ready Gemini 2.5 AI models to challenge OpenAI's enterprise dominance."
Transparency concerns: On the other hand, as mentioned above, some developers have expressed concerns that the disappearance of the "raw inference token" in Gemini 2.5 Pro (as reported by VentureBeat) may reduce transparency in understanding and debugging the operation of AI. This could be a significant issue, especially for enterprise developers.

Overall, while Gemini 2.5 is expected to be a new milestone in AI technology, many people are of the opinion that its operation and transparency require continued scrutiny.

Latest News and Roadmap Highlights (as of June 2025)

The latest development regarding Gemini 2.5 was an important announcement from Google on June 2025, 6. This information is mainly published on Google's official blogs (Google Blog and Google Developers Blog).

Gemini 2.5 Pro and Gemini 2.5 Flash are generally available (GA): These flagship models, which were previously preview versions, are now available as official versions in Vertex AI, Gemini API, and Google AI Studio. With the announcement that "Gemini 2.5 Flash and Pro are now generally available," they have become stable versions and will be fully used in production environments.
Gemini 2.5 Flash-Lite Preview Announcement: The new Gemini 2.5 family's most cost-efficient and low-latency model, Flash-Lite, is now available as a preview. It is said to be "our most cost-efficient and fastest 2.5 model yet" and is optimized for high-volume processing tasks. The "thinking" function is turned off by default, but can be controlled via API. ("thinking is turned off by default" but "enables dynamic control of the thinking budget via an API parameter").
Gemini 2.5 Flash Pricing Update: The pricing for the Flash model has changed. The price per 100M input tokens has been raised to $0.15 from $0.30, but the price per 1M output tokens has been lowered to $0.30 from $0.15. Also, the price difference for thinking vs. non-thinking has been removed.
Controlling your "thinking budget": Each Gemini 2.5 model has control over the thinking budget through an API, allowing developers to balance speed and quality of responses depending on the requirements of the task.

These updates show that Google is actively promoting the popularization and practical use of Gemini 2.5. It is expected that improvements to functions, the addition of new models, and integration into various Google services will continue in the future. It is a good idea to check the developer documentation and the official Google blog for the latest information.

Frequently Asked Questions (FAQ)

Q1: Can I use Gemini 2.5 for free?: A1: The Gemini 2.5 model itself incurs fees when developers use it through APIs, etc. The fee structure varies depending on the model (Pro, Flash, Flash-Lite) and usage. For example, Gemini 2.5 Flash has a fee structure based on input and output tokens. However, some Gemini model features may be available for free for general user services such as Google's Bard (now Gemini chatbot). Please check the official Google website for the latest availability.
Q2: Does Gemini 2.5 support Japanese?: A2: Yes, Gemini 2.5 supports multiple languages and can understand and generate Japanese. Google is aiming for global expansion, so support for major languages is progressing. Since it supports multimodal, it may be possible to handle not only Japanese text but also Japanese audio.
Q3: Do "inference model" and "thinking model" mean the same thing?: A3: They are used in almost the same sense. Both terms refer to the ability of an AI to not just memorize and output information, but to take logical steps internally, make plans, and "think" before providing an answer. The Google Developers Blog clearly states that "Gemini 2.5 models are thinking models," and this "thinking" is said to enhance reasoning capabilities.
Q4: What can I do with Gemini 2.5?: A4: It covers a wide range of tasks. For example, answering complex questions (advanced reasoning), summarizing and creating text (Flash-Lite is suitable for large-scale summarization), generating programming code (Pro is good at it), data analysis, ideation, translation, etc. It supports multimodal tasks, so it can also handle tasks related to images, audio, and video (natively understand and generate text, images, audio, video, and code).
Q5: What is the main difference between the Gemini 1.5 and previous models?: A5: The big advances in Gemini 2.5 are the introduction of "thinking processes" and the resulting significant improvement in reasoning capabilities. This allows for more complex problem solving and multi-step planning. Also new are the addition of new model variants such as Flash-Lite and the developer's finer control over the degree of "thinking". Overall, it is smarter, more flexible, and more efficient in certain tasks (e.g. Flash-Lite's low cost and low latency).

Summary and future prospects

This time, we will explain Google's latest AI "Gemini 2.5" in an easy-to-understand manner for beginners, from basic information to technical features, use cases, and the latest news. Gemini 2.5 is not just smart, but it is an AI that has entered a new dimension of "thinking." With a family of models including Pro, Flash, and the newly released Flash-Lite, it has the potential to have a major impact on our work and lives.

In particular, the improvement in its capabilities as an "inference model" has been remarkable, and it is expected to provide more advanced support for complex tasks and creative work. With multimodal support, the types of information that can be handled have increased dramatically, making the range of applications infinite.

Of course, the evolution of AI technology also brings with it ethical challenges and social acceptance. However, its potential is immeasurable. I'm excited to see how Gemini 2.5 will evolve and become integrated into our daily lives!

I hope this article helps you deepen your understanding of AI. The world of AI is constantly evolving, so keep your ears open to new information!

Disclaimer: This article is intended to provide information about AI technology and does not recommend investing in any specific products or services. Any decisions regarding the use or implementation of any technology should be made at your own risk.

[For beginners] A thorough explanation of Gemini 2.5! Will Google's "thinking AI" change the future?