Google’s Gemma Translator combines Raspberry Pi 5 and on-device AI to deliver private, offline speech translation without cloud connectivity for multilingual conversations.
Google has introduced Gemma Translator, an open-source offline speech translation system built around the Raspberry Pi 5, enabling real-time multilingual conversations without relying on cloud services or an internet connection. The handheld device processes speech entirely on-device, offering a privacy-focused alternative for users in remote locations or environments where secure communication is essential.
The system captures spoken audio through an integrated microphone before transcribing, translating and converting the response back into speech locally. It uses Google’s Gemma 4 E2B large language model running through LiteRT-LM, while Moonshine text-to-speech generates spoken translations. Once installed, the device functions independently of Wi-Fi or mobile networks, making it suitable for field operations, travel and areas with limited connectivity.
The hardware is based on an 8GB Raspberry Pi 5 and includes a 480×320 touchscreen, microphone, speaker and a custom control panel featuring push-to-talk buttons and a rotary encoder for language selection. All components are housed within a compact 3D-printed enclosure designed for portable, face-to-face conversations.
Developers created a lightweight software stack using a React-based interface and a Python API server that communicates with the local language model. A single start-up script launches the inference engine, backend and user interface, while automated deployment tools configure the system as a dedicated Raspberry Pi appliance.
The interface supports both individual and dual-user conversation modes, allowing participants to control microphones and language settings independently. During demonstrations, the device translated conversations between Spanish and Mandarin speakers, displaying translated text on-screen and delivering spoken responses without contacting external servers.
Google has released the complete project as open source, including source code, deployment scripts and 3D-printable enclosure files. The project demonstrates how advances in compact AI models and edge computing can deliver practical, private language translation entirely on local hardware, reducing dependence on cloud infrastructure while expanding access to multilingual communication.
