Google released Gemini 2.5 Pro IO edition a week before I/O - presumably to get developers testing it and build some buzz. I've been using it for Android work, and I have thoughts.
What's Different About the IO Edition
The IO edition is specifically tuned for coding tasks. Google says it has better understanding of project structure, longer context windows, and improved debugging assistance.
In practice, here's what I've noticed:
Kotlin/Compose understanding is solid. It actually suggests idiomatic Kotlin patterns instead of writing Java-style Kotlin. When I ask for Compose components, it gets state hoisting, recomposition, and modifier chains right most of the time.
Context window is noticeably longer. I can paste a whole ViewModel, Repository, and UseCase and ask questions about how they interact. Previous models would lose track of earlier code by the time I got to my question.
Debugging suggestions are specific. When I paste a stack trace, it doesn't just say "there's a null pointer exception" - it actually traces through the code to suggest where the null might originate.
How It Compares
I've been using Copilot for inline completion and ChatGPT for longer explanations. Here's where Gemini fits in:
vs. GitHub Copilot
Copilot is still better for inline autocomplete - it's faster and the suggestions flow better while typing. But when I need to explain what I want in natural language or paste a code block and ask "what's wrong with this," Gemini gives better answers.
Copilot also struggles with newer Compose patterns. It still suggests deprecated approaches sometimes. Gemini seems more up-to-date.
vs. ChatGPT (GPT-4)
ChatGPT gives more detailed explanations and is better at teaching concepts. If I want to understand why something works a certain way, ChatGPT is usually my pick.
But Gemini generates more accurate Android-specific code. ChatGPT often suggests patterns that work in theory but don't quite match how you'd actually structure an Android project. Gemini's suggestions feel like they came from someone who has actually shipped Android apps.
Where It's Actually Useful
Debugging unfamiliar errors. I've hit a few obscure Hilt and Compose errors where the standard Stack Overflow answers didn't apply. Gemini understood the context well enough to suggest relevant fixes.
Generating boilerplate. Room DAOs, Retrofit interfaces, Hilt modules - the repetitive setup code that follows patterns. Gemini handles these well and I just review/adjust as needed.
Understanding legacy code. Pasting old code and asking "what is this doing" actually works. It can trace through ViewModels, explain data flow, and identify potential issues.
Compose animations. I'm not great at Compose animations off the top of my head. Asking for specific animation effects with natural language descriptions usually gets me close to what I want.
Where It Falls Short
It hallucinates APIs. Less than ChatGPT, but it still invents methods that don't exist sometimes. Always verify.
Complex architecture decisions. It can implement patterns you describe, but it's not great at deciding which pattern is appropriate for your situation. You still need to make those calls.
Debugging timing/threading issues. For concurrency bugs, the suggestions are often too generic. These still require actual debugging with proper tools.
Latest library versions. It sometimes suggests older API versions. I've gotten Compose code that worked on 1.4 but was deprecated by 1.5.
Accessing It
It's available through Google AI Studio (free with limits), Vertex AI (pay-as-you-go), and eventually Android Studio integration.
For quick questions, AI Studio works fine. If you're using it heavily, the free tier limits will hit you pretty fast.
Pricing on Vertex:
- Free tier: 60 queries/minute
- Paid: $0.00025 per 1K input tokens
Not expensive, but it adds up if you're chatting with it all day.
The Gratitude App Case Study
One concrete example: the Gratitude app team claims they doubled their feature output using Gemini in Android Studio. Their use cases - debugging Hilt issues, learning to use profilers, setting up baseline profiles - match what I've found it good for.
The "2x productivity" claim seems optimistic for experienced developers, but for teams that are frequently hitting unfamiliar territory or ramping up on new patterns, I can see it making a significant difference.
Should You Try It?
If you're already using Copilot or ChatGPT for coding, Gemini 2.5 Pro IO is worth trying as an additional tool. It's not going to replace your existing setup, but it's noticeably better for Android-specific questions.
If you're not using any AI coding tools yet, this is a reasonable place to start - especially for Android development where the training seems more current than alternatives.
The full release is coming at I/O 2025 on May 14th, presumably with Android Studio integration. That's when it'll become truly useful for day-to-day work instead of copying and pasting into a browser tab.
Try it at Google AI Studio - select "Gemini 2.5 Pro IO" from the model dropdown.
