moonshine-ai/moonshine
Very low latency speech to text, intent recognition, and text to speech, for building voice agents and interfaces observed · 2026-08-28
Health v2 · maintenance only
89/100
- Activity 99
- Release rhythm 99
- Longevity 49
Flags: no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: 5.5
- age_days: 698
- days_rel: 9
- days_push: 9
- n_releases_24m: 23
Adoption not part of the score
10944 stars · 598 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
Moonshine Voice is an open-source on-device AI toolkit providing very low latency speech-to-text, intent recognition, and text-to-speech for building real-time voice agents and interfaces. It ships models from 1MB up to Whisper-Large-V3-beating accuracy, with a unified API across Python, JavaScript/WASM, iOS, Android, macOS, Linux, Windows, and Raspberry Pi.
Use cases
- transcribe live microphone audio to text with low latency
- build a real-time voice agent that responds while the user is still talking
- run speech-to-text entirely on-device without API keys or cloud calls
- convert text to natural speech in the browser or on mobile
- clone a custom voice from a few seconds of recorded speech
- add intent recognition to a spoken voice interface
- build a dictation or meeting-notes app with speaker-aware transcripts
When to choose
- you need low-latency streaming transcription for live voice agents
- privacy matters and audio must never leave the device
- you need one speech stack across many platforms including embedded and WASM
- you want tiny models for resource-constrained devices like Raspberry Pi
- you want MIT-licensed speech models without per-call cloud costs
When to avoid
- you need batch offline transcription of large audio archives where latency is irrelevant
- you need the widest language coverage, since streaming models focus on English and a few languages
- you require commercial use of the legacy non-streaming non-English models, which carry a non-commercial license
- you need heavy-duty NLU beyond intent recognition in a full conversational AI platform
Facets
library · maturity active
speech-recognition tts nlp machine-learning sdk speech-processing artificial-intelligence cross-platform python cpp wasm windows browser cross-platform voice-agents on-device low-latency streaming-asr voice-cloning intent-recognition dictation natural-language-processing ios android macos linux
3 sources
- readme: https://github.com/moonshine-ai/moonshine · fetched 2026-08-28 · d666f3f97157
- homepage: https://moonshine.ai · fetched 2026-08-29 · 09e9140d4977
- site_page: https://moonshine.ai/tts · fetched 2026-08-29 · 80ca4f7c7b43
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| moonshine-ai/moonshine | main | 89 |
For agents
markdown · JSON · MCP: product_card(name="moonshine-ai/moonshine")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem