We Tried Gemini 2.5 Pro Experimental and It’s Mind-Blowing!

Google DeepMind has recently unveiled its latest advancement in artificial intelligence: the Gemini 2.5 Pro (experimental) model. Within just a few hours of release, this new model has taken the AI world by storm, ranking #1 on the LMArena Leaderboard! Built upon its predecessors, this new model promises enhanced capabilities and features designed to cater to complex tasks and applications. This article explains how to access Gemini 2.5 Pro, and explores its features and performance on benchmarks, as well as real-life applications.

What is Gemini 2.5 Pro?

Gemini 2.5 Pro is the latest AI model from Google DeepMind, designed to offer improved performance, efficiency, and capabilities over its predecessors. It is part of the Gemini 2.5 series and represents the Pro-tier version, which balances power and cost-efficiency for developers and businesses.

How is Gemini 2.5 Pro Different from Gemini 1.5 Pro?

Here’s how Gemini 2.5 Pro (experimental) is more advanced than Gemini 1.5 Pro:

• It shows higher accuracy in language understanding and multimodal tasks.
• It is more efficient in computation, meaning it has a better speed and lower costs.
• Its advanced coding and reasoning capabilities make it ideal for AI developers.

Key Features of Gemini 2.5 Pro

Gemini 2.5 Pro introduces several notable enhancements:​

1. Multimodal Capabilities: Gemini 2.5 Pro supports various data types, including text, images, video, audio, and code repositories. It can thus handle a diverse range of inputs and outputs, making it a versatile tool across different domains.
2. Advanced Reasoning System: At the core of Gemini 2.5 Pro is its sophisticated reasoning system, which enables the AI to methodically analyze information before generating responses. This deliberate approach allows for more accurate and contextually relevant outputs.
3. Extended Context Window: Gemini 2.5 Pro features an expanded context window of 1 million tokens. This allows it to process and understand larger volumes of information simultaneously.
4. Enhanced Coding Performance: The model demonstrates significant improvements in coding tasks, offering developers more efficient and accurate code generation and assistance.
5. Extended Knowledge Base: Gemini 2.5 is trained on more recent data as compared to most other models, marking a knowledge cut-off at January 2025.

Google will soon make Gemini 2.5 Pro available on Vertex AI. Google also plans to launch an improved version of the model supporting a context window of 2 million tokens.

How to Access Gemini 2.5 Pro

Gemini 2.5 Pro (experimental) is currently accessible on the Google AI Studio to all and to Gemini Advanced subscribers on the Gemini app. Here’s how you can access it:

On Google AI Studio:

Developers can access Gemini 2.5 Pro through Google AI Studio by selecting the model from the model selection drop-down box.

On Google Gemini Website:

Gemini Advanced users can try out the Gemini 2.5 Pro experimental model directly on the chatbot’s web interface by selecting the model from the model selection drop-down box.

Gemini 2.5 Pro Experimental: Hands-on Testing

Now that we know how to access the model, let’s try it out ourselves and see if it stands up to the said expectations. Since only some of the multimodal features have been rolled out yet, we’ll be testing the model on the following 3 tasks:

1. Logical Reasoning
2. Image Generation
3. Image Analysis

Task 1: Logical Reasoning

We’ll first test Gemini 2.5 Pro’s advanced reasoning capabilities. For this task, I gave the model a logical reasoning puzzle to solve based on a bunch of clues.

Prompt: “There are 5 ships in a port:

1. The Greek ship leaves at six and carries coffee.
2. The Ship in the middle has a black exterior.
3. The English ship leaves at nine.
4. The French ship with blue exterior is to the left of a ship that carries coffee.
5. To the right of the ship carrying cocoa is a ship going to Marseille.
6. The Brazilian ship is heading for Manila.
7. Next to the ship carrying rice is a ship with a green exterior.
8. A ship going to Genoa leaves at five.
9. The Spanish ship leaves at seven and is to the right of the ship going to Marseille.
10. The ship with a red exterior goes to Hamburg.
11. Next to the ship leaving at seven is a ship with a white exterior.
12. The ship on the border carries corn.
13. The ship with a black exterior leaves at eight.
14. The ship carrying corn is anchored next to the ship carrying rice.
15. The ship to Hamburg leaves at six.

Which ship goes to Port Said? Which ship carries tea?

(Note: ‘to the right’ means anywhere on the right side from the given point, not only right next to. Likewise for left.)”

Response:

Review:

Firstly, Gemini 2.5 Pro shows its entire thought process. Unlike most thinking models that show their thought process as continuously typing a response, Gemini 2.5 Pro shows it in batches – one step at a time, but in detail. This makes it easier for us to follow.

The model breaks down the puzzle and explains the reasoning in numbered steps, making it easier for the user to follow and understand. It begins with a table and fills in the info after analyzing each clue. Finally, not only does it deduce the right answer, it also gives a table that can be exported to Google Sheets.

Task 2: Image Generation

Now let’s see how well Gemini 2.5 Pro (experimental) can generate images.

Prompt: “Create an image of a sunset at the beach viewed through a full-height glass window of a living room.”

Response:

Review:

Google’s Gemini 2.5 Pro (experimental) has created a beautiful and realistic image following the prompt. The textures of the furniture and the difference in lighting prove the model’s contextual understanding and creativity. I am truly impressed with this response!

Task 3: Image Analysis

Prompt: “Explain the image.”

Input Image:

Response:

Review:

Gemini 2.5 Pro understands the image and explains it accurately and in great detail. It can read the text in images, follow arrows and markings, as well as contextually understand visual content. The model’s image analysis capabilities can help students learn better and more easily by breaking down complex diagrams into simple explanations.

Google Gemini 2.5 Pro (Experimental): Benchmark Performance

Now let’s have a look at how well the model has performed in standard benchmark tests.

1. Reasoning & Knowledge (Humanity’s Last Exam):

Gemini 2.5 Pro (experimental) achieves a score of 18.8% on this benchmark, significantly outperforming other popular models such as OpenAI’s GPT-4.5, Anthropic’s Claude 3.7 Sonnet, X.AI’s Grok 3 Beta, and DeepSeek-R1. This shows its strong capabilities in complex reasoning tasks, particularly when operating without external tools.

2. GPQA Diamond (Science):

Gemini 2.5 Pro tops the benchmark, scoring 84%. It outperforms GPT-4.5 by a margin of almost 5%, and all other models significantly. This indicates its strong capabilities in scientific reasoning and knowledge application.

3. Mathematics (AIME 2025):

Google’s Gemini 2.5 Pro achieves a score of 86.7% on this math benchmark, which is nearly identical to OpenA’s GPT-4.5 (86.5%). At the same time, it significantly surpasses Claude 3.7 Sonnet and Grok 3 Beta. However, it is notably outperformed by DeepSeek R1, which scores 93.3% on this specific test.

4. LMArena:

On the LM Chatbot Arena, Google’s Gemini 2.5 Pro (experimental) leads the board with a score of 1443, which is significantly higher than Grok-3 Preview at 2nd place with 1404 points. This shows the new model to be quite promising, especially for real-life coding tasks.

Here are some more benchmark scores of Google’s Gemini 2.5 Pro experimental model, proving its enhanced capabilities.

Applications of Gemini 2.5 Pro

The advanced features of Gemini 2.5 Pro open up numerous applications across various industries:​

• Software Development: With its enhanced coding capabilities, developers can leverage Gemini 2.5 Pro for code generation, debugging, and providing real-time assistance during the development process.​
• Data Analysis: The model’s ability to process large datasets makes it suitable for complex data analysis tasks, enabling organizations to derive insights and make informed decisions more effectively.​
• Content Creation: Gemini 2.5 Pro’s support for multiple data types allows content creators to generate and refine text, images, videos, and audio content, streamlining the creative process.​
• Conversational AI: The advanced reasoning system enhances the quality of interactions in chatbots and virtual assistants, providing users with more accurate and context-aware responses.​

Conclusion

The introduction of Gemini 2.5 Pro marks a significant milestone in Google’s AI advancements. With its enhanced reasoning abilities, extended context processing, and multimodal features, the model is poised to be a multifunctional AI tool across industries. As organizations and developers begin to integrate Gemini 2.5 Pro into their workflows and applications, it is expected to drive innovation and elevate the standards of AI applications across the board.

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Sabreena is a GenAI enthusiast and tech editor who’s passionate about documenting the latest advancements that shape the world. She’s currently exploring the world of AI and Data Science as the Manager of Content & Growth at Analytics Vidhya.