Moonshine is a suite of speech-to-text models optimized for resource-constrained devices, making it ideal for real-time, on-device applications such as live transcription and voice command recognition. It outperforms the OpenAI Whisper model of the same size in word error rate (WER) on test datasets used in the OpenASR leaderboard maintained by HuggingFace. Additionally, Moonshine's computational requirements vary with the length of the input audio, allowing for quicker processing of shorter audio compared to the Whisper model, which processes everything in 30-second chunks. Moonshine processes 10-second audio segments at a speed five times faster than Whisper while maintaining the same or better WER.