Gemini 2.5 is a next-generation language model developed by Google and regarded as a significant advancement in the field of artificial intelligence. This model stands out particularly for its "reasoning" capabilities, designed to solve complex problems. The first model in the Gemini 2.5 family, Gemini 2.5 Pro, is distinguished by its enhanced reasoning, coding, and multimodal abilities (processing various data types such as text, images, sound, and video). Google has described it as "the smartest artificial intelligence model" and introduced it on March 25, 2025.

Technical Features of Gemini 2.5 Pro

Gemini 2.5 Pro is a multimodal artificial intelligence model, meaning it can process different types of data such as text, images, sound, and video. The model has been released with a context window of 1 million tokens, equivalent to approximately 750,000 words, allowing it to process a single text longer than the entire "The Lord of the Rings" series by J.R.R. Tolkien. It is planned to increase this capacity to 2 million tokens shortly. For outputs, it supports up to 64,000 tokens. The model's knowledge cut-off date is January 2025, and it can produce structured outputs with tool usage like function calls.

^{Gemini 2.5 Pro (Google)}

The most striking feature of Gemini 2.5 Pro is its "reasoning" ability. Unlike traditional models, this model conducts analysis, performs logical inferences, and considers context before answering a question. According to Google DeepMind CTO Koray Kavukcuoğlu, this ability has been achieved by significantly improving the base model and combining it with enhanced post-training techniques. The model has been made accessible in the Gemini app for Google AI Studio and Gemini Advanced subscribers and will soon be available on the Vertex AI platform.

Performance and Comparative Analysis

Gemini 2.5 Pro demonstrates superior performance in various benchmarks compared to its competitors. Below, the results and comparisons in basic tests of the model are presented in detail:

1. Reasoning and Knowledge (Humanity’s Last Exam): In this multimodal test, Gemini 2.5 Pro scored 18.8%, surpassing leading models such as OpenAI's o3-mini (14.0%), GPT-4.5 (6.4%), Claude 3.7 Sonnet (8.9%), and DeepSeek R1 (8.6%). The test includes questions prepared by thousands of experts in fields like mathematics, humanities, and natural sciences.
2. Mathematics (AIME 2024 and 2025): In the American Mathematics Competition (AIME) tests, Gemini 2.5 Pro scored 92.0% in AIME 2024 and 86.7% in AIME 2025 on a single trial. These results surpass models such as Claude 3.7 Sonnet (83.9% and 77.3%) and Grok 3 Beta (79.8% and 70.0%), while closely competing with OpenAI o3-mini (87.3% and 86.5%).
3. Science (GPQA Diamond): In the scientific reasoning test, Gemini 2.5 Pro leads with an 84.0% score. It surpasses models like Claude 3.7 Sonnet (78.2%) and Grok 3 Beta (80.2%), approaching Anthropic's 84.8% in multiple trial results.
4. Coding (SWE-bench Verified and Aider Polyglot): In the agent-based coding test (SWE-bench Verified), Gemini 2.5 Pro with 63.8% surpasses OpenAI o3-mini (49.3%) and DeepSeek R1 (49.2%) models but falls short of Claude 3.7 Sonnet's 70.3% score. In the code editing test (Aider Polyglot), it provides superior scores of 74.0% (full) and 68.6% (difference) compared to its competitors.
5. Visual Reasoning (MMMU): In the multimodal visual reasoning test, Gemini 2.5 Pro scored 81.7%, outperforming models like OpenAI GPT-4.5 (74.4%) and Claude 3.7 Sonnet (75.0%). OpenAI o3-mini and DeepSeek R1 do not offer multimodal support.
6. Long Context (MRCR): Gemini 2.5 Pro, achieving scores of 91.5% in the 128k token test and 83.1% in the 1M token test, outperforms its competitors in long-context processing capacity.

These results demonstrate that Gemini 2.5 Pro offers wide competencies in areas such as mathematics, science, coding, and multimodal reasoning. However, falling behind in certain tests (e.g., SWE-bench Verified) of Claude 3.7 Sonnet suggests that there is potential for further improvement in specific areas.

^{Gemini 2.5 Pro Benchmark Score (Google)}

Innovative Features and Applications

Gemini 2.5 Pro stands out especially in coding and complex problem-solving. The model can produce run-ready video games (e.g., a dinosaur game) or interactive web applications with a single-line command. It also has superior abilities in creating visually impressive web applications and agent-based coding projects. These features prove that the model is strong not only in theory but also in practical applications.

^{Gemini 2.5 Dinosaur Game (Google DeepMind)}

The model's long context window increases its capacity to analyze large datasets (such as entire code repositories or long texts), and its multimodal structure offers more comprehensive solutions by combining information from different data types. Google indicates that these capabilities will play a key role in developing AI agents, systems that can autonomously perform tasks without human intervention.

Limitations and Future Perspectives

The high performance of Gemini 2.5 Pro is achieved through "reasoning" techniques that require additional computation power and time, indicating that the model is a more expensive option. Google has not yet disclosed API pricing details but announced that it will share this information in the coming weeks. Furthermore, the model's experimental status implies that more testing and optimization are required before full commercial use.

In the future, Google plans to integrate reasoning capabilities into all its new models. This could increase the capacity of artificial intelligence to solve more complex problems, accelerating the development of agents with high context awareness. However, the security and ethical dimensions of these developments must also be considered. Google emphasizes its commitment to responsible development in the "agent age."

The Gemini 2.5 Pro Experimental is an innovative model that combines reasoning and multimodal processing capacity in AI technologies. Its superior performance in mathematics, science, and coding, long context window, and success in practical applications make it a strong contender against competitors like OpenAI, Anthropic, and DeepSeek. However, cost and limitations in certain tests show that the model's development process is ongoing. Gemini 2.5 Pro has the potential to form the basis of autonomous systems and complex problem-solving tools in the future of AI and can be considered a milestone that will pave the way for further research in this field.