Gemini 2.5 Pro, announced by Google in March 2025, is the company's latest and most advanced large language model.

In the rapidly advancing generative AI competition, its performance and features are attracting significant attention.

This article explains the following three perspectives for general users:

• Latest topics and notable points
• Historical background of Google's LLM development
• Technical features unique to Gemini 2.5 Pro

Latest Topics and Notable Points

Google's Highest Performing Model to Date

Gemini 2.5 Pro is the highest-performing AI model developed by Google at the time of its release.

Its advanced reasoning ability, characterized as a "thinking AI model," is its most significant feature.

It possesses problem-solving capabilities that exceed previous models, and its performance has been highly evaluated from various sectors.

In fact, it achieved the top position in the rankings of the AI benchmark evaluation site "LLM Arena" immediately after its release.

The result, which outperformed competing models from the same period in terms of performance, has caused a significant reaction in the industry.

Performance Comparison with Competing Models

According to expert evaluations, Gemini 2.5 Pro's reasoning ability surpasses that of other companies' latest models.

It recorded higher scores than the latest models from OpenAI and Anthropic in benchmarks measuring knowledge and logical thinking ability.

In mathematics and science fields, it achieved a high score of 86.7% on the high school-level equivalent AIME 2025.

Based on these achievements, comparisons between major models such as "GPT-4.5 vs. Gemini 2.5" have become a topic of discussion in various media.

Use Cases Domestically and Internationally

Gemini 2.5 Pro has begun to be put into practical use in various scenarios immediately after its release.

Google has begun providing Gemini 2.5 Pro to developers through "Google AI Studio".

It was initially released as a preview version, with integration into the enterprise Vertex AI service also planned.

Third-Party Utilization

JetBrains incorporated Gemini 2.5 Pro into its AI assistant.

This has significantly improved the accuracy of code auto-completion and bug detection.

According to the company, it enables "more accurate and context-aware code suggestions," which is expected to improve development efficiency.

Future Development Predictions

Full-scale introduction into Google's own services is still at the preview stage.

In the future, integration with the search engine, Gmail, and Google Documents is anticipated.

Improvements in search accuracy and intelligent document summarization leveraging its excellent reasoning capabilities are predicted.

Thus, Gemini 2.5 Pro is attracting attention as Google's trump card to make a comeback in the generative AI competition.

Its rapid evolution in a short period has also become a topic of discussion, with various media reporting that "Google's AI development is accelerating."

History of Google's Language Model Development

2018: The Emergence of BERT

In 2018, Google's research team announced the language model "BERT".

This is evaluated as a groundbreaking breakthrough in natural language processing.

BERT achieved bidirectional contextual understanding through the Transformer architecture.

It possessed performance comparable to human reading comprehension and was an innovative model focusing on text understanding.

It is also known for dramatically improving the interpretation accuracy of queries when introduced to Google Search.

2021: Development of LaMDA

LaMDA emerged as a large language model specializing in dialogue.

Google first unveiled LaMDA at its developer conference in May 2021, which created a significant response.

A characteristic feature was the ability to continue natural conversations, not just specific question and answer sessions.

It was highly evaluated and attracted attention for its naturalness, similar to casual conversation with humans.

In 2022, a Google engineer at the time sparked a temporary controversy by stating that "AI has begun to have consciousness."

2022: Birth of PaLM

Based on the achievements of LaMDA, Google developed PaLM (Pathways Language Model).

It was designed as an ultra-large-scale model with approximately 540 billion parameters.

It had a wide range of capabilities including multilingual support, translation, advanced reading comprehension, and common sense reasoning.

Mathematical reasoning ability was also improved by incorporating specialized data such as mathematical papers into the learning process.

It also possessed the ability to generate and complete programming code, and its high practicality was evaluated.

In 2023, the improved version PaLM 2 appeared, with reports of understanding subtle nuances in over 100 languages and strength in logical quizzes.

2023: Initiation of the Gemini Project

Following the success of ChatGPT, Google sought to make a comeback in the field of conversational AI.

It was also during this period that the company's internal AI research division and DeepMind merged to form "Google DeepMind."

Under this strengthened structure, Gemini was developed as a next-generation multimodal AI.

Gemini 1.0, the first version, was announced in December 2023.

A characteristic feature was its multimodal design that could understand not only text but also images and videos.

Evolution Process of Gemini

Gemini 1.0 began with internal testing and experimental introduction to some services.

In February 2024, the enhanced version Gemini 1.5 Pro was released.

As the name suggests, performance and functions were improved, and it was also adopted for the dialogue service "Bard."

The LLM used in Bard evolved from the initial LaMDA to PaLM, PaLM 2, and was updated to Gemini Pro.

This enabled understanding of image input and advanced reasoning, improving the user experience.

2024-Present: Rapid Evolution

Gemini 2.0 was announced in late 2024.

Functional aspects were significantly improved, including enhanced reasoning capabilities and support for processing lengthy contexts.

Then in March 2025, the latest model Gemini 2.5 Pro was experimentally released.

In just over a year, the Gemini series has rapidly evolved, with the acceleration of AI development becoming evident.

Gemini 2.5 Pro can be said to be the culmination of Google's LLM development.

Research results since BERT (high-efficiency learning, dialogue-specific technology, reinforcement learning, etc.) have been consolidated.

Technical Features of Gemini 2.5 Pro

Functions of a "Thinking AI Model"

The most significant feature of Gemini 2.5 Pro lies in its reasoning ability that seems to "think".

While previous LLMs were also capable of reasoning, Gemini 2.5 Pro has evolved further.

It generates logical and consistent answers through a design that handles the reasoning process itself within the model.

Google positions it as a "thinking model," emphasizing the step-by-step thought process.

Its ability to reach answers by following intermediate steps even for difficult problems is highly evaluated.

High Benchmark Performance

It also recorded high scores on the challenging test "Humanity's Last Exam" created by experts.

It achieved a then top-class correct answer rate of 18.8% without additional tools.

While this may seem like a low figure, it is a remarkable achievement for a difficult test that measures "the frontier of human knowledge that AI cannot contend with."

It demonstrates top-class performance in knowledge and reasoning problem benchmarks.

It demonstrates a presence leading the industry as a "thinking AI."

Advanced Coding Capabilities

Gemini 2.5 Pro also excels in handling programming code.

While previous models were also capable of code generation, Gemini 2.5 Pro goes a step further.

It has the ability to execute, verify, and improve the code it generates itself.

It can automatically build working programs for given tasks.

Achievements in Development Support Benchmarks

It has achieved excellent results in software development benchmarks.

It surpassed OpenAI's GPT-4.5 and approached Claude 3.7 in results.

It recorded a high correct answer rate of 63.8% on SWE-Bench.

It is also good at automatic UI generation for web applications and code conversion between languages.

In actual demos, it has also demonstrated the ability to generate complete game code from simple instructions.

Native Multimodal Support

Multimodal support is integrated into the basic design of Gemini 2.5 Pro.

It can directly understand various forms of information including not only text but also images, audio, and video.

If shown a photo and asked for an explanation, it analyzes the content and responds with text.

Transcription and summarization of audio data have also become easy to perform.

Superiority in Multimodal Processing

Unlike other models, its strength lies in being able to handle image analysis and speech recognition in an integrated manner rather than as an afterthought.

Google has previously emphasized the importance of multimodal AI.

Gemini 2.5 Pro can process multiple input formats simultaneously to answer questions.

It can respond at once to complex queries such as "Tell me the recipe from this food photo."

Ultra-Large Capacity Context Processing Ability

Gemini 2.5 Pro has also significantly improved its ability to process long texts and large amounts of information.

The input length (context window) that can be processed at once has been expanded to 1 million tokens.

Support for 2 million tokens is also planned for the future, with further evolution expected.

Practical Benefits of Long Text Processing

1 million tokens corresponds to several million characters in Japanese, exceeding the volume of a book.

This large capacity processing has made it possible to summarize enormous documents at once.

It also has the ability to extract related information across multiple documents.

Conventionally, split processing would have been necessary, but the elimination of this trouble is a significant advantage.

It allows conversation to continue while maintaining a long dialogue history, enabling responses that take context into account.

Processing Speed and Infrastructure Optimization

Despite its high functionality, it is designed with consideration for processing speed (response speed).

The internal structure is optimized to operate with low latency despite the model's scale.

It is also suitable for uses that require immediate response, such as dialogue applications.

Currently, there are request limitations at the testing stage, but further optimization is expected in the future.

In the future, it is expected to function at high speed behind smartphone apps and web services.

API Provision and Extensibility

Gemini 2.5 Pro is also intended for use from external software via API.

Developers can incorporate this model into their own apps to add advanced functions.

Functions such as text generation, question answering, and data analysis can be easily implemented.

Currently, enterprise customization functions are not provided.

However, Google is planning to expand services by positioning this model at the core of its cloud AI infrastructure.

Main Uses of Gemini 2.5 Pro

The main uses leveraging the technical features of Gemini 2.5 Pro are as follows:

• Question Answering: Provides accurate answers in context, from general knowledge to specialized knowledge.
• Multimedia Summarization: Concisely summarizes the content of text, audio, and video. Ideal for extracting key points from meeting minutes and research papers.
• Text Generation Support: Creates articles, stories, email drafts, etc. Styles and lengths can be freely adjusted.
• Coding Support: Generates code from natural language and also suggests error corrections. Significantly improves development efficiency.
• Data Analysis: Analyzes and visualizes trends in complex data. Useful for extracting business insights.

Future Prospects

Gemini 2.5 Pro is evaluated as a significant advancement in general-purpose AI technology.

Its future range of applications is vast due to its high reasoning power, multi-functionality, and flexibility.

It will support our lives and work as a smart assistant and AI tool for specialized fields.

Google has indicated a policy of advancing integration with its own services, and the day when it permeates our daily lives may be near.

Great expectations are also placed on future updates and new applications.