What we measured and what we ship. Every number on this page is taken from the model itself: parameter counts read from the shipped ONNX graphs, timings from a warm CPU at batch one.
Four neural networks in sequence. Text is encoded; a duration model decides how long each sound lasts; a flow-matching field sculpts random noise into a mel-spectrogram in eight fixed Euler steps; and a vocoder turns that spectrogram into a 44.1 kHz waveform. The field is the only iterative stage; everything else runs once.
Built on open foundations: an open flow-matching speech model with MIT-licensed inference code and Open RAIL-M weights, which we export to ONNX, optimize, and serve. Our contribution is the inference and serving stack; attribution is retained per those licenses. The remaining ~18M parameters are a style encoder used offline to build voices, never run at synthesis time.
Most diffusion systems need tens to hundreds of network passes per utterance: roughly ~1,000 for high-quality diffusion, ~50 for fast variants. Because the flow path is nearly straight, eight suffice. That, plus a network small enough to keep its weights in cache, is the whole trick.
Not an illustration: a real utterance, its spectrogram plotted star for star. Hear every voice in the voice gallery, or synthesise your own in the dashboard.
An RTF of 0.18 on a commodity core is the whole business case. A GPU serving realtime voice runs at batch one, its worst case, and idles most of its silicon; a CPU at batch one is doing exactly the work it is good at. The floor that collapses is the price: feather at $1.90 per million characters, 0.19¢ per 1,000, and it holds in every region, inside your own cloud, on-premise, and air-gapped.
At list prices, feather is roughly 8× cheaper than Polly, 19× cheaper than Cartesia, and up to 50× cheaper than frontier voice models. Per minute of audio: $0.0017, about 15 paise; per hour, $0.10. Competitor rates are published list prices and move; starling per-minute is derived from the same characters-per-minute assumption as feather. Full detail on the pricing page.
Both instruments are serving. feather is the cheap, fast workhorse for agents and high-volume narration; starling is the expressive flagship for cloning, media, and lifelike agents. Same endpoint, same keys, one line of difference in the request.
Both run on ordinary CPUs, so either model deploys in any region, inside your own cloud, or fully on-prem. Neither exposes an emotion or expression control: register comes from the voice you pick, the punctuation, and the phrasing.