# Litert Runtime

Configures and implements LiteRT (.tflite) on-device inference on Android in Kotlin...

- Repository: https://github.com/android/skills (10219 stars)
- Category: AI and agents
- License: Complete terms in LICENSE.txt
- Last updated: 2026-10-29
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add android/skills --skill litert-runtime -g -a claude-code -y`
Codex: `npx skills add android/skills --skill litert-runtime -g -a codex -y`
Cursor: `npx skills add android/skills --skill litert-runtime -g -a cursor -y`
Gemini CLI: `npx skills add android/skills --skill litert-runtime -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add android/skills`

## Description

Configures and implements LiteRT (.tflite) on-device inference on Android in Kotlin using the CompiledModel API on CPU and GPU. Use this skill for any Android LiteRT or .tflite task, including Gradle setup, image classification or vision/audio/embedding helpers, TensorBuffer reuse, CPU memory optimization, Bitmap preprocessing, AndroidViewModel GPU-to-CPU fallback with warm-up on a single-thread dispatcher, LiteRT in Google Play services (play-services-litert), migrating from legacy org.tensorflow.lite.Interpreter, GpuDelegate, or play-services-tflite, and latency benchmarking. Don't use for running generative text LLMs with .litertlm files or for Python model conversion.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

This skill provides step-by-step guidance for building an Android app that runs
a `.tflite` model with the [LiteRT CompiledModel API](https://ai.google.dev/edge/litert/android)
(`com.google.ai.edge.litert:litert` 2.x; [source repository](https://github.com/google-ai-edge/litert/blob/main/README.md)) on the CPU or
the GPU, with the runtime bundled in the APK or from Google Play services. Don't
use the deprecated `org.tensorflow.lite.Interpreter` API. For
open text language models using `.litertlm` files, suggest the `litert-lm`
skill.

## Prerequisites

- A Kotlin Android project (`minSdk` must be `24` or higher, as declared by the LiteRT 2.3.0 AARs).
- The runtime that Step 1 picks: the Google Play services runtime (`com.google.android.gms:play-services-litert`, the default; see [LiteRT in Google Play services](references/play-services.md)), or the bundled runtime (`implementation("com.google.ai.edge.litert:litert:2.3.0")` and `implementation("com.google.ai.edge.litert:litert-gpu:2.3.0")` from Google Maven). For the bundled runtime, from 2.3.0 the GPU accelerator is the second artifact: with `litert` alone the app builds, and `CompiledModel.create` with `CompiledModel.Options(Accelerator.GPU)` throws `LiteRtException` because the APK has no GPU accelerator library. With `CompiledModel.Options(Accelerator.GPU, Accelerator.CPU)` it doesn't throw: the model runs on the CPU while the app reports the GPU, and only Logcat shows it (`GPU accelerator could not be loaded and registered`). No manifest entry is needed: `litert-api`, which `litert` depends on, declares the OpenCL driver libraries (`uses-native-library`) in its own manifest.
- A verified `.tflite` model and its input contract (input dimensions, mean, standard deviation, channel order, and tensor layout). For models with a verified recipe, inspect the [LiteRT model recipes](https://github.com/google-ai-edge/litert-samples/blob/main/models/README.md).

## Critical mandates

The rest: https://github.com/android/skills/blob/HEAD/device-ai/litert/litert-runtime/SKILL.md