LinnetTTS
Lightweight on-device text-to-speech: flow LM over a continuous-latent codec, Rust runtime, Android/iOS/Linux/Python
Get picks like this daily. Today's launch numbers, the top launches, AI and tech news, and a daily opportunity pick, straight to your inbox.
GITHUB · launched Nov 3, 2026 · 24 upvotes (top 89%) · 0 views
Niche: speech and voice ai models · 136 launches, 9 in the last 7 days · Explore this niche →
Category and tags
- Horizontal
- Model & infra
- Developer
- AI-native
- Hobby / open-source project
- android
- ios
- java
- kotlin
- linux
- on-device
- +6 more
Visit website ↗ Source listing ↗
Could you build this?
No The product is a custom on-device TTS model built on a flow language model and neural codec, which requires ML research, training data, and compute.
What it would actually take: A real version needs a neural codec for continuous latents, a flow-matching language model trained on large speech corpora, and an optimized inference runtime with quantization for mobile CPUs. The hard parts are the model research and training data, and the expertise is in speech ML and efficient on-device inference.
Competitors
Other products that read as similar to this one : 3193 launches clear the similarity bar, closest 8 shown.
Attention rank: #2911 of 3194 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).
Launched 369 days after the earliest competitor.
- Inflect TTS v2+ONNX, 9M/4M text-to-speech models running in the browser · hn · 2026-07-26 · 7 upvotes · similarity 0.73
- Eloqium-TTS · github · 2026-09-11 · 6 upvotes · similarity 0.72
- ito · github · 2026-10-02 · 11 upvotes · similarity 0.71
- Voxxy · hn · 2026-05-24 · 9 upvotes · similarity 0.71
- persian_tts · github · 2026-09-16 · 125 upvotes · similarity 0.68
- phonon · github · 2026-11-01 · 26 upvotes · similarity 0.67
- Speko · ph · 2026-08-27 · 266 upvotes · similarity 0.65
- ai-phone · github · 2026-10-27 · 347 upvotes · similarity 0.65
The niche, labels, vibe code rating and competitor comparison on this page are analysis by Nicheloom. If you use them, please credit nicheloom.com. How you may use our data.