Gemini 2.5 Pro Preview: Best AI Coding Tool For Developers

Google’s latest iteration of its powerful AI model, Gemini 2.5 Pro Preview (I/O Edition), has arrived ahead of schedule. It boasts significant enhancements in coding capabilities, particularly for web development. There are also new video understanding functionalities. This release is already making waves, topping leaderboards and promising to streamline developer workflows.

This updated Gemini 2.5 Pro Preview model is designed with developers in mind. It offers meaningful improvements in frontend and UI development, code transformation and editing, and the creation of sophisticated agentic workflows. It maintains the same pricing as its predecessor, ensuring accessibility to its cutting-edge features.

From improved code editing tools to multi-step agent capabilities, the new model is tailored to developers building interactive applications.

Key Takeaways

Enhanced Coding Prowess: Gemini 2.5 Pro Preview demonstrates significantly improved coding capabilities, especially in web development, frontend/UI tasks, with better multi-step agent workflows. It now leads the WebDev Arena leaderboard.
Advanced Multimodality: The model introduces state-of-the-art video understanding, enabling innovative workflows like transforming video content into interactive learning applications.
Developer-Focused Improvements: Addressing key feedback, this version reduces errors in function calling. It also improves trigger rates. This makes it a more reliable tool for complex coding tasks.

Gemini 2.5 Pro now ranks #1 on LM Arena, beating OpenAI’s o3 and Anthropic’s Claude 3.7 Sonnet.

What’s new with Gemini 2.5 Pro Preview?

The primary focus of this upgrade is a marked improvement in coding performance. It aims to enhance its excellent coding capabilities. The special focus is on web development to create much better looking web apps.

Learn more: Build rich, interactive web apps with an updated Gemini 2.5 Pro

The enhancements are not limited to just aesthetics. Developers can expect meaningful improvements for front-end and UI development. There are also improvements in fundamental coding tasks like transforming and editing code.

They can create sophisticated agentic workflows. These refer to AI systems (agents) that can execute sequences of tasks. They make decisions and use tools to achieve a complex goal. This functions much like a human assistant. For example, an AI agent could take a user order to plan a trip. It would then break the order down into finding flights, booking accommodation, and suggesting an itinerary. Different tools would be used for each step.

This is clear when comparing the new version to its predecessor. For example, in a test, Gemini 2.5 Pro was benchmarked directly against its earlier version using a fantasy sports dashboard prompt. The updated model produced a more detailed layout. It improved the fantasy sports league manager dashboard.

Both models showed strong reasoning chains and output quality. However, the newer version produced cleaner, more optimized HTML/CSS and integrated more features in one pass.

The updated model took slightly more time (60s vs 50s) but delivered richer results, especially when rendering in HTML editors. The upgrade wasn’t just speed—it was clarity and intent.

Learn more about this test here:

A standout new feature is its advanced video understanding.

Gemini 2.5 Pro can now take a YouTube video and, based on its content, generate an interactive learning application. This showcases a significant leap in multimodal capabilities. This means the AI can understand and process information from multiple types of input, like text, images, audio, and video. It can also generate output in various formats.

Gemini 2.5 Pro’s ability to create a learning app from a video is a prime example of its multimodal strength.

The model scored an impressive 84.8% on the VideoMME benchmark, highlighting its state-of-the-art performance in this area.

This opens up possibilities for “transforming videos into interactive applications,” making learning from video content more engaging and effective.

Here are its video understanding benchmarks:

Furthermore, Google has addressed crucial developer feedback, leading to “reducing errors in function calling and improving function calling trigger rates.”

In AI models, function calling is the ability to interact with external tools and APIs by “calling functions.” For example, the model could call a weather API to get current weather information. It could also call a calculator tool to carry out a complex calculation. Improved function calling means the AI is more reliable in using these external resources and efficient for complex, multi-step tasks.

Learn more about its video capabilities here: Advancing the frontier of video understanding with Gemini 2.5

Benchmark performance – Gemini 2.5 Pro vs Claude 3.7 Sonnet and OpenAI o3

Key advantages of Gemini 2.5 Pro:

UI-friendly generation: Better alignment with frontend frameworks.
Chain-of-thought transparency: Developers can follow how it reasons.
Stronger multi-modal input support, including video-to-text capabilities.

Gemini 2.5 Pro Preview isn’t just claiming improvements; it’s proving them on recognized industry benchmarks. It has quickly ascended to the #1 spot on the WebDev Arena leaderboard. This leaderboard measures a model’s ability to create functional and aesthetically pleasing web applications. Gemini 2.5 Pro Preview has surpassed the prior leader, Claude 3.7 Sonnet.

The model holds the top position on the overall LM Arena rankings. It outperforms OpenAI’s o3 model across multi-modal tasks. It also excels in coding and UI reasoning tasks.

These rankings are significant as they show human preference and real-world applicability. Testimonials from industry collaborators further underscore its capabilities.

Silas Alberti from Cognition stated,

The updated Gemini 2.5 Pro achieves leading performance on our junior-dev evals. It was the first-ever model that solved one of our evals involving a larger refractor of a request routing backend.

Similarly, Michael Truell, CEO of Cursor, an AI coding tool, noticed an improvement with the new model. He observed a “significant reduction in its failure to call tools.”

Gemini 2.5 Pro Preview: Pros, Limitations, and Use Cases

Pros of Gemini 2.5 Pro Preview

Leading Coding Capabilities: Excels in frontend/UI development, code editing, and generating aesthetically pleasing and functional web apps.
State-of-the-Art Video Understanding: Opens new avenues for interactive content creation and learning from video.

Improved Reliability: Reduced errors in function calling make it more dependable for complex agentic workflows. It also provides transparent reasoning steps.
Large Context Window: It can process vast amounts of information. In the context of Large Language Models (LLMs), text is broken down into smaller units called tokens. These can be words, parts of words, or characters. The “context window” of a model is often measured in tokens. It refers to the amount of information the model can consider at one time. This includes both input and output. Gemini 2.5 Pro boasts a large 1 million token context window, with plans to expand to 2 million. Currently, it handles 1 million tokens but will soon handle 2 million. This ability is crucial for large codebases and comprehensive document analysis.
Competitive Pricing: The updated model is available at the same price as the previous version.

Strong Benchmark Performance: Top rankings on WebDev Arena and LM Arena confirm its capabilities against competitors.

Limitations of Gemini 2.5 Pro Preview

Preview Stage: As a “Preview” or “Experimental” model, it may still have occasional unexpected behaviors or errors. For example, I saw YouTube reviews where it is getting stuck in a loop on a highly complex task during a re-test.
Real-world Complexity: While benchmarks are useful, real-world software development involves much larger and more intricate codebases. The true test will be its performance in such complex, long-term projects.

Resource Allocation: Initial performance in terms of speed can sometimes be affected by resource allocation for new preview models.
Lacks broader public-facing interface like ChatGPT

How to use Gemini 2.5 Pro Preview – top use cases

Frontend Apps: Rapidly prototype interfaces with working JavaScript/HTML/CSS code.
Video Summarization: Transform YouTube clips into interactive study tools.
Workflow Automation: Generate multi-step logic chains for agent-based models that interact with other tools and services.
Education Tech: Transforming educational video content into engaging, interactive learning experiences. For example, you can use its video understanding to create quizzes or breakdowns from visual content.

Dev Tooling: Integrate with AI Studio to test, compare, and refine outputs.
Web Application Development: Rapidly creating and iterating on web UIs, from simple landing pages to more complex dashboards.
Code Generation and Transformation: Assisting developers in writing, refactoring, and debugging code across various programming languages.

Automated Content Creation: Generating animations or other visual content from video inputs.
Data Analysis and Summarization: Processing and understanding large documents or codebases due to its extensive context window.

Gemini 2.5 Pro Preview pricing

The Gemini 2.5 Pro Preview (I/O edition) continues to be available at the same price as the previous iteration. Developers can access it via the Gemini API through Google AI Studio and Vertex AI.

Here’s the pricing table:

Gemini 2.5 Pro Preview developer API pricing table

Source: Gemini Developer API Pricing

This pricing keeps it lower than competitors like GPT-4 Turbo and Claude’s commercial plans. It is an ideal pick for startups and mid-size developer teams.

Google AI Studio usage itself is generally free in available countries. The API offers a “free tier” with lower rate limits for testing.

Action Points: How to use Gemini 2.5 Pro Preview

Explore Google AI Studio: If you haven’t already, get hands-on with Gemini 2.5 Pro Preview through Google AI Studio. It’s a great environment for experimenting with its capabilities, including the new video-to-code features.

Test on Your Coding Projects: Integrate the model into your existing development workflows. Try it for UI generation, code refactoring, or building out new features.
Experiment with Multimodal Prompts: Explore its ability to understand and process video and image inputs. Use these inputs alongside text for more creative and complex applications.
Build Agentic Workflows: Leverage the improved function calling and reasoning to create more sophisticated AI agents that can automate tasks.

Give Feedback: As this is a preview release, developer feedback is crucial for Google to continue refining the model.
Scale: Evaluate pricing vs token needs if scaling your app.

Frequently Asked Questions on Gemini 2.5 Pro Preview

What are the main improvements in Gemini 2.5 Pro Preview?

Key improvements include stronger coding for frontend/UI. They also feature better code transformation and editing. Another advancement is the creation of agentic workflows. Moreover, it includes new video understanding skills. It also has reduced errors in function calling.

Is Gemini 2.5 Pro free to use?

No, but it offers affordable token-based pricing starting at $0.0025 per 1M tokens.

How does it compare to Claude or GPT-4 Turbo?

In coding and UI tests, Gemini 2.5 Pro leads in both performance and reasoning clarity.

Does it support multi-modal inputs?

Yes—images, video, and text inputs are all supported.

Is AI Studio needed to use Gemini?

No, but it’s the most effective way to test and compare models.

What’s the main difference from Gemini 1.5?

Improved frontend generation, deeper agent workflow design, and video comprehension.

Where can I test Gemini 2.5 Pro Preview?

Use AI Studio for direct testing.

Is there a mobile version of the Gemini 2.5 Pro Preview API?

Currently, usage is limited to API and web-based tools.

Can Gemini 2.5 Pro Preview be used for writing?

Yes, though it’s particularly strong in structured, technical content like code.

What’s unique about Gemini 2.5 Pro Preview reasoning engine?

It shows “chain-of-thought” logic, so developers can see how it arrived at a solution.

Does Gemini 2.5 Pro Preview support Google Cloud integration?

Yes, via the Vertex AI platform.

Will Gemini 3 replace the Gemini 2.5 Pro Preview soon?

There’s no public timeline, but Gemini 2.5 Pro remains top-tier in benchmarks at the point of writing this guide.

Is Gemini 2.5 Pro Preview better at coding than the previous version?

Yes, early tests and benchmarks show significant improvements in coding, particularly in generating more detailed and aesthetically pleasing web applications.

How can developers access Gemini 2.5 Pro Preview?

Developers can access it via the Gemini API through Google AI Studio and Vertex AI.

What is the context window size for Gemini 2.5 Pro?

It features a 1 million token context window, with Google planning to increase it to 2 million tokens

Where does Gemini 2.5 Pro stand on video understanding benchmarks?

It scored 84.8% on the VideoMME benchmark, demonstrating state-of-the-art capabilities.

Has there been any feedback from early adopters?

Yes, companies like Cognition and Cursor have reported positive results. They noted its leading performance on developer evaluations. The tool also shows improvements in use.

Will this model replace the previous Gemini 2.5 Pro?

The previous iteration now points to this most recent version. Developers using the previous version will automatically benefit from the improvements.

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