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title: Bring any idea to life with Gemini 3 and Firebase AI Logic
description: Gemini 3 Pro preview is now available to mobile and web developers through Firebase AI Logic client SDKs on the Blaze plan, enabling secure client-side AI...
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# Bring any idea to life with Gemini 3 and Firebase AI Logic

**[Firebase](https://daily.dev/sources/firebase-blog)** · 4 min read · 0 upvotes · 0 comments

## Summary

Gemini 3 Pro preview is now available to mobile and web developers through Firebase AI Logic client SDKs on the Blaze plan, enabling secure client-side AI features without server setup. The SDKs automatically handle thought signatures across turns, support the new higher-resolution default for input media (with a configurable parameter coming soon), and will soon add thinking-level controls alongside existing thinking budgets. Firebase also offers an AI monitoring dashboard for tracking latency, costs, and usage, plus integrations with App Check and Remote Config for security and dynamic updates across Android, Flutter, Web, iOS, and Unity.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://firebase.blog/posts/2025/11/gemini-3-firebase-ai-logic>

## Questions this post answers

### How do I use Gemini 3 Pro preview in a Firebase app?

Specify gemini-3-pro-preview as the modelName when initializing a generative model through Firebase AI Logic client SDKs. This works across Android, Flutter, Web, iOS, and Unity on the Blaze plan, giving direct client-side access to the Gemini API without needing server-side setup, and supports configuring thinkingConfig with includeThoughts and a temperature value.

_daily.dev surfaces practical Gemini integration guides for developers wiring AI into client apps._

### What are thought signatures in Gemini 3 and do I need to manage them manually?

Thought signatures are encrypted representations of Gemini 3's internal thought process, included in the thought_signature field of response content parts like text, functionCall, and inlineData. They preserve thought context across conversation turns. Firebase AI Logic client SDKs handle these automatically, so no manual orchestration is required to maintain context between turns.

_developers building multi-turn AI features track model behavior changes like this via daily.dev._

### Why did Gemini 3 increase token usage and latency in my app compared to older models?

Gemini 3 introduces a new default higher resolution for multimodal input processing via the media_resolution parameter, which improves the model's ability to read fine text and identify small details but increases token usage and latency as a tradeoff. A configurable parameter to control input media resolution in client SDKs is planned but not yet released.

_teams debugging AI cost and latency tradeoffs follow model changes like this on daily.dev._

## Similar posts on daily.dev

- [Build smarter apps with Gemini 3 Flash](https://daily.dev/posts/build-smarter-apps-with-gemini-3-flash-rgootmsr4) · Android Developers Blog · 76 upvotes · 2 comments
- [Serverless AI for Android with Firebase AI Logic](https://daily.dev/posts/serverless-ai-for-android-with-firebase-ai-logic-33d7pefc4) · ProAndroidDev · 0 upvotes · 0 comments

---

Tags: [#mobile](https://daily.dev/tags/mobile), [#genai](https://daily.dev/tags/genai), [#firebase](https://daily.dev/tags/firebase)

[View this post on daily.dev](https://daily.dev/posts/bring-any-idea-to-life-with-gemini-3-and-firebase-ai-logic-wgeyntpsx)

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