We Tried the Google 2.5 Pro Experimental Model 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.

Also Read: Gemini 2.0 – Everything You Need to Know About Google’s Latest LLMs

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: The model 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: It 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: It is trained on more recent data as compared to most other models, marking a knowledge cut-off at January 2025.

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

Also Read: Gemini 2.0: Google’s New Model for the Agentic Era

How to Access Gemini 2.5 Pro

Gemini 2.5 Pro (experimental) is currently available on the Google AI Studio to everybody for free. It is also accessible 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 Experimental 03-25 through Google AI Studio by selecting the model from the model selection drop-down box.

The model on Google AI Studio offers extensive multimodality, where you can upload text documents, YouTube video links, and even external files from Google Drive. You can also use the camera feature to click an input image or record a video to add to your prompt. The platform even lets you record audio clips to prompt the model.

On Google Gemini Website:

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

Also Read: I Tried All the Latest Gemini 2.0 Model APIs for Free!

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. We’ll be testing the model on the following 5 tasks:

1. Logical Reasoning
2. Image Generation
3. Image Analysis
4. Video Analysis
5. Audio Analysis

Since only some of the multimodal features have been rolled out on the web interface yet, we’ll be trying out the last 2 tasks on Google AI Studio. So, let’s get started!

Also Read: GPT 4o vs Gemini 2.0 Flash vs Grok 3 for Image Generation

Task 1: Logical Reasoning

We’ll first test the model’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, the model showed 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.

For this task, the model broke down the puzzle and explained the reasoning in numbered steps, making it easier for me to follow and understand. It began with a table and filled in the info after analyzing each clue. Finally, not only did it deduce the right answer, it also gave me a table that can be exported to Google Sheets.

Task 2: Image Generation

Now let’s see how well the model 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:

The model 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!

Also Read: OpenAI’s 4o Image Generation is SUPER COOL

Task 3: Image Analysis

In this task, we’ll explore the model’s image analysis capabilities.

Prompt: “Explain the image.”

Input Image:

Response:

Review:

The model understood the image and explained it accurately and in great detail. It could 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.

Also Read: Is o3-mini Better Than o1 for Image Analysis?

Task 4: Video Analysis

Now let’s witness the model’s performance in video analysis. For this, I’m going to ask it to create a social media post for me based on a YouTube short.

Prompt: “Write me a LinkedIn article based on the content of this video.”

Input Video: Debunking the Biggest Myths About AI in 2025!

Response:

Review:

The model took just about 16 seconds to understand the minute-long video, and another 5 seconds to write the article. The generated LinkedIn post was well-written and comprehensive, covering all the points mentioned in the video. This showcases the model’s prowess in video analysis, contextual understanding, and creative writing.

Task 5: Audio Analysis

I’ve been waiting to try out the audio analysis feature on this new model. I have an audio clip generated by Google’s Gemma 2, which I’m going to ask Gemini 2.5 Pro to summarize.

Prompt: “Give me a 100-word summary of what’s discussed in the audio clip.”

Input Audio: Gemma 2_ Google’s Open-Source AI Disruptor That Punches Above Its Weight

Response:

Review:

That was simply amazing! This 11 minute long audio clip was processed and summarized in just 18 seconds! The model generated a concise summary, including all the important points, while staying within the suggested word limit of 100.

Performance Summary

Here’s a summary of the model’s performance across all the tasks we’ve tried out.

All of these multimodal features unlock a wide range of applications for Gemini 2.5 Pro across industries. Its versatility makes it a powerful tool for diverse use cases, from content creation to complex problem-solving

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, Gemini-2.5-Pro-Exp-03-25 leads the board with a score of 1443, which is almost 40 points more than Grok-3 Preview at 2nd place with 1404 points. Meanwhile, Gemini’s 2.0-Pro-Exp-02-05 is at 4th place with a score of 1380. This shows the new model to be quite promising, especially for real-life coding tasks.

Here are some more benchmark scores of the 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 the model 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: It supports multiple data types, which 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. Now that you know how to access Gemini 2.5 Pro, do try it out and let us know your experience and review in the comments.

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K.C. Sabreena Basheer

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.