# Mastering Edge AI on Raspberry Pi with LiteRT and Gemma

DevFeed: [Mastering Edge AI on Raspberry Pi with LiteRT and Gemma](<https://devfeed.tech/articles/mastering-edge-ai-on-raspberry-pi-with-litert-and-gemma-4215.md>)

Original publisher: [Read original article](<https://developers.googleblog.com/mastering-edge-ai-on-raspberry-pi-with-litert-and-gemma/>)

Author: Lu Wang; Terry Heo; Naushir Patuck; José María Casanova

Published: 2026-09-12T11:04:33.891311Z

Content type: tutorial

Language: en

Sources: [Google Developers Blog](<https://devfeed.tech/sources/google-developers-blog.md>)

Topics: [LiteRT](<https://devfeed.tech/topics/litert.md>), [On-device AI](<https://devfeed.tech/topics/on-device-ai.md>), [Local AI](<https://devfeed.tech/topics/local-ai.md>), [AI, ML & Data Engineering](<https://devfeed.tech/topics/ai-ml-data-engineering.md>), [Google AI](<https://devfeed.tech/topics/google-ai.md>), [cpu](<https://devfeed.tech/topics/cpu.md>), [Security, Privacy and Abuse Prevention](<https://devfeed.tech/topics/security-privacy-and-abuse-prevention.md>)

Tags: [cli](<https://devfeed.tech/tags/cli.md>), [cpu](<https://devfeed.tech/tags/cpu.md>), [edge](<https://devfeed.tech/tags/edge.md>), [gemma](<https://devfeed.tech/tags/gemma.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [inference](<https://devfeed.tech/tags/inference.md>), [litert](<https://devfeed.tech/tags/litert.md>), [offline](<https://devfeed.tech/tags/offline.md>), [on-device](<https://devfeed.tech/tags/on-device.md>), [real-time](<https://devfeed.tech/tags/real-time.md>), [robotics](<https://devfeed.tech/tags/robotics.md>)

## AI overview

The article explains how to deploy Gemma models with LiteRT on a Raspberry Pi for local, real-time edge AI applications such as robotics. It highlights LiteRT-LM, CPU and GPU optimization, and reported performance figures for Gemma 4 E2B on Raspberry Pi 5.

## Source excerpt

Deploying secure, real-time Edge AI on Raspberry Pi is now simplified using LiteRT and lightweight Gemma open models. LiteRT optimizes CPU and GPU performance, delivering fast token speeds for models like Gemma4, enabling real-time local reasoning for robotics. Developers can quickly convert, quantize, and run these models using the lightweight LiteRT CLI tool. Support for Hailo AI accelerators is also coming very soon.