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Firebase AI Logic

by GoogleMountain View, California, USANo ratings yet

Call Gemini models directly from mobile and web apps via Firebase

Visit firebase.google.com

Linked from firebase.google.com · checked 28 Oct

Tool type
Managed Firebase service for client-side Gemini API calls
Made for
Mobile and web app developers
Runs on
Android, Apple, Flutter, Unity and web apps
Model calls are made from the app client; configuration is managed in the Firebase console.
Last checked
28 Oct 2026
2 product sources

What it does

Firebase AI Logic is a managed Firebase service that lets mobile and web apps call the Gemini API through client SDKs, without writing a separate backend in another language. Developers provide app inputs such as text, images, audio, and video, and the service returns model-generated output to the app. Prompts, model configuration, system instructions, and output schemas can be stored on Firebase servers and updated from the Firebase console without shipping a new app version.

People typically use it to add AI chat, personalization, image generation, and tool features like Grounding with Google Search or Google Maps to an app. Its distinguishing features are hybrid inference, which can run on-device models when available and fall back to cloud models, plus App Check protection for Gemini calls, per-call monitoring of latency and token usage, and support for the Live API for conversational audio and video.

It suits app developers building for Apple, Android, Flutter, Unity, or web who already use Firebase. Getting started requires enabling the Gemini API provider in the Firebase console, and usage is billed according to current Google Cloud or Gemini Developer API pricing. Limits include reliance on those external pricing schedules and on-device availability that varies by platform.

What it can do

  • Calls Gemini models from Android, iOS, Flutter, Unity, and web client SDKs
  • Hybrid inference that uses on-device models when available and falls back to cloud-hosted models
  • Stores prompts, model configuration, system instructions, and output schemas on Firebase servers for updates without app releases
  • Monitors each Gemini API call in the Firebase console, including latency and token usage with traces
  • Supports the Gemini Live API for conversational audio and video experiences
  • Integrates Grounding with Google Search and Google Maps tools

Works with

  • Firebase App Check
  • Cloud Storage for Firebase
  • Firebase Security Rules
  • Cloud Functions for Firebase
  • Model Armor
  • Firebase Remote Config

Example workflows

In-app AI chat with managed prompts
Input: user messages typed in a mobile or web app. Steps: store the system instruction and model configuration in Firebase, call Gemini through the client SDK, and monitor latency and token usage in the console. Output: chat replies shown in the app, with traces available for unexpected responses.
Image-based feature with file uploads
Input: a user-selected photo uploaded to Cloud Storage for Firebase with Security Rules limiting access. Steps: send the image and a prompt through the client SDK, optionally using Cloud Functions to enforce rate limits or block keywords. Output: generated text or image output returned to the app.

Before you choose

  • Billing is handled through current Google Cloud or Gemini Developer API pricing, so model costs are separate from the free Firebase service.
  • On-device inference depends on the device and platform; cloud fallback applies when no on-device model is available.
  • Model Armor safety protections apply when accessing Gemini through the Gemini Enterprise Agent Platform.

Listed under

Get started

Setup starts in the Firebase console, then an app integrates the SDK.

  1. In the Firebase console, enable the Gemini API provider for your project.
  2. Add the Firebase AI Logic SDK to your Android, iOS, Flutter, Unity, or web app and make a first Gemini call.
  3. Turn on Firebase App Check and configure Firebase Security Rules for any files your AI features access.
Enable the Gemini API provider in the Firebase console

Plans and prices

Prices in USD

Firebase AI Logic is described as a no-cost service, billed according to current Google Cloud or Gemini Developer API pricing. The page does not state per-token or per-request model rates; consult the linked Firebase AI Logic pricing documentation for current charges.

Usage-based model billingUsage-basedSee the Firebase AI Logic pricing docs for current rate table.
  • Billed per current Google Cloud or Gemini Developer API pricing
  • Service described as no-cost

Source: firebase.google.com/pricing, checked 28 Oct 2026. Prices can change; check before you buy.

Sources for this overview

Product pages, documentation, and pricing checked 28 Oct 2026. Each source supports part of the overview; availability and prices can change.

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Last checked 28 Oct 2026. Every field keeps its source and date; unknown means we couldn’t confirm it.