Get started with MediaPipe Tasks

MediaPipe Tasks provides cross-platform APIs and prebuilt pipelines for running vision, text, audio, retrieval, and decision models directly on-device. Every task pairs an end-to-end runtime pipeline with hardware-accelerated execution across Web, Android, iOS, Python, and Flutter.

To test tasks interactively before writing code, launch MediaPipe Web Demos, browse Samples & Demos, or jump directly to any task guide for a live Web SDK playground and platform Quickstart tabs.

MediaPipe Tasks 3-step integration flow
Consistent API

Three steps across platforms

Install the domain package, initialize the task with a .task, .tflite, or .litertlm model bundle, and run inference on images, video frames, text, or audio streams.

Hardware Acceleration

End-to-end CPU and GPU pipelines

MediaPipe Tasks handles input preprocessing, tokenization, model execution, and structured post-processing on-device for low-latency real-time applications.

Model asset placement & threading

Every MediaPipe task loads a .task bundle, .tflite model, or .litertlm checkpoint via BaseOptions. Place your model file in the standard asset location for your target platform:

  • Android: Place .task, .tflite, or .litertlm files in your module's src/main/assets/ directory (for example, app/src/main/assets/hand_landmarker.task) and pass the filename to BaseOptions.builder().setModelAssetPath("hand_landmarker.task").
  • iOS: Add the model file to your Xcode application target bundle (verified under Build Phases > Copy Bundle Resources) and resolve its runtime path with Bundle.main.path(forResource:ofType:).
  • Web: Serve the model from your application's static public directory or a CDN URL and pass the URL to baseOptions.modelAssetPath (or pass a Uint8Array / ReadableStreamDefaultReader to baseOptions.modelAssetBuffer).
  • Python: Pass the local filesystem path to BaseOptions(model_asset_path="...").
  • Flutter: List Google's pinned models under hooks.user_defines in pubspec.yaml, run dart run mediapipe_core:bundle_models to bundle them into assets/mediapipe/, and pass the model to the task options (for example, FaceLandmarkerOptions(model: VisionModels.faceLandmarker)). To use your own model, pass modelPath or modelBytes instead. See Bundle models.

Supported platforms

Choose a platform to add the MediaPipe Tasks SDK to your project across all five task domains (Vision, Text, Audio, Retrieval, and Decision), read the complete setup guide for each environment, and see Prepare input data to format vision and audio media for inference.

Web and JavaScript

Install the npm package for your domain (@mediapipe/tasks-vision, @mediapipe/tasks-text, @mediapipe/tasks-audio, @mediapipe/tasks-retrieval, or @mediapipe/tasks-decision) or import its ESM bundle from a CDN. See the Web setup guide and JavaScript API reference.

npm install @mediapipe/tasks-vision @mediapipe/tasks-text @mediapipe/tasks-audio @mediapipe/tasks-retrieval @mediapipe/tasks-decision

Android

Add the Maven dependency for your domain in Gradle. See the Android setup guide and Java API reference.

Android (Kotlin)

dependencies {
  implementation("com.google.mediapipe:tasks-vision:latest.release")
  implementation("com.google.mediapipe:tasks-text:latest.release")
  implementation("com.google.mediapipe:tasks-audio:latest.release")
  implementation("com.google.mediapipe:tasks-retrieval:latest.release")
  implementation("com.google.mediapipe:tasks-decision:latest.release")
}

Android (Java)

dependencies {
  implementation 'com.google.mediapipe:tasks-vision:latest.release'
  implementation 'com.google.mediapipe:tasks-text:latest.release'
  implementation 'com.google.mediapipe:tasks-audio:latest.release'
  implementation 'com.google.mediapipe:tasks-retrieval:latest.release'
  implementation 'com.google.mediapipe:tasks-decision:latest.release'
}

iOS

Add MediaPipe Tasks using Swift Package Manager in Xcode or Package.swift. See the iOS setup guide and Swift API reference.

// Package.swift (Swift Package Manager)
dependencies: [
    .package(url: "https://github.com/google-ai-edge/mediapipe", branch: "master"),
],
targets: [
    .target(
        name: "MyAppTarget",
        dependencies: [
            .product(name: "MediaPipeTasksVision", package: "mediapipe"),
            .product(name: "MediaPipeTasksText", package: "mediapipe"),
            .product(name: "MediaPipeTasksAudio", package: "mediapipe"),
            .product(name: "MediaPipeTasksRetrieval", package: "mediapipe"),
            .product(name: "MediaPipeTasksDecision", package: "mediapipe"),
        ]
    ),
]

Python

Install the mediapipe package with pip and import the task modules for desktop, server, or notebook workflows. See the Python setup guide and Python API reference.

# python -m pip install mediapipe
import mediapipe as mp
from mediapipe.tasks import python
from mediapipe.tasks.python import audio, decision, retrieval, text, vision

Flutter

Add the package for your domain (mediapipe_vision, mediapipe_text, mediapipe_audio, mediapipe_retrieval, or mediapipe_decision) from pub.dev. The same Dart API runs on Android, iOS, macOS, Linux, Windows, and the web. See the Flutter setup guide.

flutter pub add mediapipe_vision mediapipe_text mediapipe_audio mediapipe_retrieval mediapipe_decision