# Speech recognition that runs on the device 11 August 2026 · Ritesh Bonthalakoti Ritesh working through the models one at a time on the Uno Q. Every speech API works the same way. A microphone captures audio, the audio goes to a server, text comes back a moment later. ElevenLabs, Sarvam, Google's — they are all good at it, and they all assume that trip is fine. For something sitting in a kitchen, it isn't. ## Why not just call an API? The round trip costs time. A device that answers a beat late reads as broken, and you cannot explain a user out of that impression. The audio is somebody's home. Once it has left the building, whatever governs it is a promise rather than a fact. And the network is not always there. A cloud-backed device does not slow down when the connection drops — it stops understanding anything at all. Those are the hours ours are built for. ## What Ritesh tried The constraint was the board, not the model. Plenty runs on a workstation with a graphics card. The question was what runs on something that could sit inside a product, which in this case meant an Arduino Uno Q. Moonshine, Vosk, Whisper. Those were the local models worth taking seriously at that size, so he benchmarked them. ## What worked Faster-Whisper, the small model — about 244 million parameters — running on the board itself. No API key. No round trip. Nothing to fail when the connection does. ## What it doesn't prove yet One board and one model is not a product, and we are not going to pretend it is. We are still experimenting with other combinations of board and model. But we say that where a device of ours listens, the listening happens on the device and the audio stays there. ## Related reading - [On-device speech-to-text for VAHA: the model, where transcription happens, and a first accuracy test](https://dharanova.com/whitepapers/vaha-on-device-speech-to-text.md) a whitepaper from our lab - [Wake-word and stop-phrase detection for VAHA: dataset, validation accuracy and first field check](https://dharanova.com/whitepapers/vaha-wake-word-stop-phrase-detection.md) a whitepaper from our lab - [On the device or in the cloud?](https://dharanova.com/learn/on-device-vs-cloud.md) background on Learn [Read the post on LinkedIn](https://www.linkedin.com/posts/dharanova_dharanova-pioneer-focusing-on-tts-and-stt-activity-7492821938617090049-RDxS) [All updates](https://dharanova.com/updates.md)