Reachy Mini goes fully local

After building your Reachy Mini, you'll install the conversation app and start talking to it. Until now, you had to send your audio to a server. But not anymore. Today we'll walk you through running the whole stack locally.

This stack is powered by speech-to-speech, our cascaded VAD → STT → LLM → TTS pipeline that exposes a Realtime API-compatible /v1/realtime WebSocket. Once you launch the backend, point the robot at it from the UI.

Cascades are the most flexible option in the open-source landscape today, and with the right pieces they're also the fastest. We'll recommend the components we like best, but the whole point of a cascade is that you can swap them. New models drop every week.

TL;DR

Deploy a local speech backend for your Reachy Mini.

We use our speech-to-speech library, a cascade approach.

Recommended: llama.cpp with Gemma 4, Silero VAD, Parakeet-TDT 0.6B v3 STT, Qwen3-TTS.

Quick start

This blog walks you through running conversations with Reachy Mini fully locally. No cloud, no API keys, no data leaving your machine. Here's a video showing this live:

Locally serving the LLM

To serve the LLM, we'll use Hugging Face's llama.cpp. If you need to install it, the simplest way is brew install llama.cpp or winget install llama.cpp, for more help, check the docs. First, we'll run:

llama-server -hf ggml-org/gemma-4-E4B-it-GGUF -np 2 -c 65536 -fa on --swa-full

And done! The first time it will download the model, subsequent launches are fast.

What do those flags do?

Setting up speech-to-speech

We'll begin by simply installing the library

uv pip install speech-to-speech

Then, while we are serving the LLM in another terminal, we can simply run:

speech-to-speech --responses_api_base_url "http://127.0.0.1:8080" --responses_api_api_key "" --mode local

And you can start talking to the model through your terminal! The first time it will need to download Parakeet-TDT 0.6B v3 and Qwen3TTS, but subsequent launches are fast.

Here's a video showing the local conversation mode: