Open source speech foundation model that runs locally on CPU in real-time

We’ve just released Neuphonic TTS Air, a lightweight open-source speech foundation model under Apache 2.0.

The main idea: frontier-quality text-to-speech, but small enough to run in realtime on CPU. No GPUs, no cloud APIs, no rate limits.

Why we built this: - Most speech models today live behind paid APIs → privacy tradeoffs, recurring costs, and external dependencies. - With Air, you get full control, privacy, and zero marginal cost. - It enables new use cases where running speech models on-device matters (edge compute, accessibility tools, offline apps).

Repo: https://github.com/neuphonic/neutts-air

Would love feedback from HN on performance, applications, and contributions.

I tried it today, amazing quality but VERY slow. took nearly 2 mins to generate audio for a single sentence on an M1 mac

Really cool, all my experiments with local speech has been spotty. Keen to try this out.

Can it run on a gpu? Would it be faster?

So basically kokoro, but VC backed? Both models use espeak, so it seems like it’s the same general approach.

Demo sounds great.

How does this compare to Piper?

Appears to use a proprietary codec as well.

From the examples it seems that every time you run it, it clones a voice from the samples folder. Is there any way to compile this so it doesn't happen every time?

Sorry if I'm missing the point.