Google has just released a new upgraded version of their Gemini model, the Gemini 2.5 Pro 065 update. This latest iteration boasts enhanced capabilities in coding, reasoning, science, and mathematics. Notably, the Gemini 2.5 Pro has seen a significant 24-point ELO score jump on the LMA Marina leaderboard, maintaining its lead at 1470. Additionally, it has a 35-point ELO jump to the lead on the WebDev Arena at 1443.

The model continues to excel at coding, leading on difficult benchmarks like Adar Polyot. It has also improved greatly in terms of its styling and structure, resulting in more creative and formatted responses. Compared to other proprietary models like OpenAI's O3, O4, Mini, Cloud 4, Opus, Brock 3 Beta, and the new Deepseek R1, the Gemini 2.5 Pro is either beating or closely matching them in almost every benchmark.

One notable change is that the Gemini 2.5 Pro's code generation is slightly better in the ADR Polyot benchmark than the Cloud 4 Opus. However, in terms of agent capabilities, it is slightly behind many of the other models, including the Opus 4, by approximately 10 points.

In terms of pricing, the Gemini 2.5 Pro is listed at $1.25 for 1 million input tokens with no caching, and $10 for 1 million output tokens. This makes it significantly cheaper than the other models, though not as cheap as the Deepseek R1.

The Gemini 2.5 Pro is now available through Google's Gemini app, the Google AI Studio, and the Vert.Ex AI platform. Additionally, users can access a free API through Kilo Code, which offers a Gemini 2.5 Pro API key with $100 in free tokens, or through the Questy API provider.

The Gemini 2.5 Pro model has seen a significant improvement in its benchmark scores compared to its previous version. It has achieved a 24-point ELO score jump on the LMA Marina leaderboard, maintaining its lead at 1470. Additionally, it has a 35-point ELO jump to the lead on the WebDev Arena at 1443.

In terms of coding capabilities, the Gemini 2.5 Pro continues to excel, leading on difficult benchmarks like the Adar Polyot. The model has also improved greatly in its styling and structure, resulting in more creative and formatted responses.

When compared to other proprietary models like OpenAI's O3, O4, Mini, Cloud 4, Opus, Brock 3 Beta, and the new upgraded Deepseek R1, the Gemini 2.5 Pro is either beating or closely matching these models in almost every benchmark.

One notable improvement is in the ADR Polyot benchmark, where the Gemini 2.5 Pro performs better than the Cloud 4 Opus. However, in terms of agent capabilities, the model is slightly behind many of the other models, including the Opus 4, by approximately 10 points.

In terms of pricing, the Gemini 2.5 Pro is listed at $1.25 for 1 million input tokens with no caching, and $10 for 1 million output tokens. This makes it significantly cheaper than the other models, though not as cheap as the Deepseek R1.

Overall, the Gemini 2.5 Pro has taken a significant leap forward in its capabilities, particularly in the areas of coding, reasoning, science, and mathematics. While it may not match the agent capabilities of some of the other models, its improved performance, lower pricing, and availability through various platforms make it a compelling option for those looking to leverage its capabilities.

The Gemini 2.5 Pro model is listed at a competitive price point compared to other AI models on the market. The input price is set at $1.25 for 1 million input tokens, with no caching. For 1 million output tokens, the price is listed at $10. This pricing structure makes the Gemini 2.5 Pro a more affordable option compared to models like the OpenAI's O3 and O4, which can be significantly more expensive.

In terms of accessibility, the Gemini 2.5 Pro model has been integrated into Google's Gemini app, allowing users to access and chat with the model directly within the app. Additionally, the API for the Gemini 2.5 Pro is readily available, making it easy for developers to integrate the model into their applications.

For those who may not have the resources to access the API directly, the model can also be accessed through third-party providers like Kilo Code and Questy API. Kilo Code offers a Gemini 2.5 Pro API key with $100 in free tokens, and Questy API also provides an option to access the model.

Overall, the Gemini 2.5 Pro's competitive pricing and multiple access points make it a compelling choice for those looking to leverage advanced AI capabilities in their projects or applications.

The Gemini 2.5 Pro model has demonstrated significant improvements in its coding, reasoning, science, and mathematics capabilities. In this section, we'll showcase its abilities in creating a SaaS landing page, an SVG-based butterfly, and an animated data visualizer.

SaaS Landing Page

The Gemini 2.5 Pro model was able to quickly generate a visually appealing SaaS landing page, complete with a main placeholder for an image, a "Powerful Features" section, testimonials, and a pricing page. The model also added a background animation to the landing page when prompted, showcasing its ability to enhance the design and interactivity of the page.

SVG Butterfly

Next, the model was tasked with creating an SVG-based butterfly. The resulting output demonstrates the model's artistic capabilities, with a well-formed and visually appealing butterfly design. The SVG format allows for scalable and customizable vector graphics, which is a valuable asset for various design and visualization applications.

Data Visualizer

Finally, the model was challenged to create an SVG-based data visualizer that can smoothly animate transitions when the underlying data changes. The model successfully generated a data visualizer with bar charts, line charts, and pie charts, allowing for the dynamic display of different data sets. This showcases the model's ability to handle data visualization tasks and create interactive, responsive user interfaces.

Overall, the Gemini 2.5 Pro model has proven its versatility in tackling a wide range of tasks, from front-end development to data visualization and creative design. Its enhanced capabilities in coding, reasoning, and structured output generation make it a valuable tool for developers and designers alike.

The Gemini 2.5 Pro model has demonstrated impressive capabilities in coding, reasoning, science, and mathematics. In this section, we will leverage its abilities to build a React-based chatbot UI with features like typing indicators, message streaming, and Markdown format support.

The chatbot will be powered by the OpenAI API, utilizing the Gemini 2.5 Pro model's enhanced performance in comparison to other proprietary models like O3, O4 Mini, and Cloud 4 Opus.

To get started, we will create a React application that incorporates the necessary components for the chatbot UI. The application will allow users to change themes and stream responses from the OpenAI API, which will be accessed using the Gemini 2.5 Pro model's API key.

The chatbot will feature a clean and intuitive interface, with the ability to display messages in Markdown format and provide typing indicators to enhance the user experience. The data visualization capabilities of the Gemini 2.5 Pro model will also be showcased, as the chatbot will be able to generate SVG-based charts and graphs to present data in an engaging and interactive manner.

Overall, this project will demonstrate the Gemini 2.5 Pro model's versatility and its ability to power advanced applications, leveraging its strengths in coding, reasoning, and data visualization to create a compelling and user-friendly chatbot experience.

The Gemini 2.5 Pro is a significant upgrade to Google's Gemini model, boasting enhanced capabilities in coding, reasoning, science, and mathematics. The model has seen a 24-point ELO score jump on LMA Marina, maintaining its lead on the leaderboard at 1470, and a 35-point ELO jump to the lead on WebDev Arena at 1443.

The Gemini 2.5 Pro excels at coding, leading on difficult benchmarks like Adar Polyot, and has also improved greatly in terms of its styling and structure, allowing for more creative and formatted responses. While it is slightly behind some other proprietary models in agent capabilities, it is significantly cheaper, making it a more accessible option for many users.

One of the standout features of the Gemini 2.5 Pro is its ability to handle large context windows, making it well-suited for working with large codebases. Additionally, its improved capabilities in math, science, and reasoning make it a versatile tool for a wide range of applications.

To get started with the Gemini 2.5 Pro, users can access it through the Google AI Studio or use the API provided by Vert.Ex AI. For those with limited resources, Kilo Code and Questy API also offer free API access with credits to get started.

Overall, the Gemini 2.5 Pro is a powerful and cost-effective model that delivers exceptional performance across a variety of domains, making it a compelling choice for developers, researchers, and anyone in need of advanced AI capabilities.