TTSLab
Test TTS & STT models in your browser. No server required.
What it does
TTSLab lets you run and compare TTS & STT models directly in your browser using WebGPU and WASM — no server, no API keys, no data collection. Your text and audio never leave your device. Run Kokoro 82M, Whisper, Moonshine, and more. Models are downloaded once and cached locally. Compare voices side by side, run benchmarks, or chat with a Voice Agent — all on-device. Built for developers, researchers, and product teams. Fully open source (MIT).
Does the same job
all alternatives →- KTKitten TTS – 25MB CPU-Only, Open-Source TTS Model2025 · github.com · ▲1,003
Kitten TTS is an open-source series of tiny and expressive text-to-speech models for on-device applications. We are excited to launch a preview of our smallest model, which is less than 25 MB. This model has 15M parameters. This release supports English text-to-speech applications in eight voices: four male and four female. The model is quantized to int8 + fp16, and it uses onnx for runtime. The model is designed to run literally anywhere eg. raspberry pi, low-end smartphones, wearables, browsers etc. No GPU required! We're releasing this to give early users a sense of the latency and voices…
- TATTSLab – A voice AI agent and TTS lab running in the browser via WebGPUFeb 2026 · ttslab.dev · ▲5
I built TTSLab — a free, open-source tool for running text-to-speech and speech-to-text models directly in the browser using WebGPU and WASM. No API keys, no backend, no data leaves your machine. When you open the site, you'll hear it immediately — the landing page auto-generates speech from three different sentences right in your browser, no setup required. You can then try any model yourself: type text, hit generate, hear it instantly. Models download once and get cached locally. The most experimental feature: a fully in-browser Voice Agent. It chains speech-to-text → LLM → text-to-speech,…
- TNThree new Kitten TTS models – smallest less than 25MBMar 2026 · github.com · ▲561
Kitten TTS (https://github.com/KittenML/KittenTTS) is an open-source series of tiny and expressive text-to-speech models for on-device applications. We had a thread last year here: https://news.ycombinator.com/item?id=44807868. Today we're releasing three new models with 80M, 40M and 14M parameters. The largest model (80M) has the highest quality. The 14M variant reaches new SOTA in expressivity among similar sized models, despite being <25MB in size. This release is a major upgrade from the previous one and supports English text-to-speech applications in…
- MOMoonshine Open-Weights STT models – higher accuracy than WhisperLargev3Feb 2026 · github.com · ▲316
I wanted to share our new speech to text model, and the library to use them effectively. We're a small startup (six people, sub-$100k monthly GPU budget) so I'm proud of the work the team has done to create streaming STT models with lower word-error rates than OpenAI's largest Whisper model. Admittedly Large v3 is a couple of years old, but we're near the top the HF OpenASR leaderboard, even up against Nvidia's Parakeet family. Anyway, I'd love to get feedback on the models and software, and hear about what people might build with it.
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