The top comment on the r/LocalLLaMA thread about Gradium's new speech model was not about the speech.
"Ohhhhh this Phonon is a different Phonon than this Phonon."
The reply under it: "Yea, this definitely won't cause any confusion whatsoever."
That, more than any benchmark, is the mood of this launch. Gradium, a Paris speech company spun out of Kyutai, open-sourced a family of text-to-speech models on 20 October 2026.
Two sizes. Phonon 31m and Phonon 40m. Both small enough to run offline on hardware you already own.
i read that thread twice. Not for the specs. For the confusion.
There was already a Phonon out in the world. Speech to text, also for edge devices, from a different company.
So for the first two days, a chunk of the internet was excited about, or annoyed at, the wrong model.
The tech underneath is the part worth caring about. A 64.5 MB file that speaks English in 6.9 milliseconds on a laptop CPU is not a normal thing to download.
Kokoro was the last "wait, that's it?" moment at 82 million parameters. This is under half that.
But the packaging is messy in a way that will cost somebody money.
Here is what actually shipped, and the part that annoyed me.
The size question nobody answers cleanly
here's a question people always ask when a model this small drops: how is it this small?
The honest answer is that the number on the box is not the number you install. Phonon is a flow-matching transformer. It predicts audio latents in 80 millisecond frames, then hands them to Kyutai's Mimi codec to decode into sound.
The 31 million parameters count the transformer. They do not count the audio tokenizer on the other end.
So "31M" is real, and it is also a partial figure. The full working setup is heavier than the headline.
Not by much. Enough that a memory budget planned straight off the model card will surprise you at deploy time.
The repo lists 64.5 MB for the q8 GGUF. That file is the whole English checkpoint, and it runs faster than real time on a Raspberry Pi 5.
i used to think parameter counts were the useful number. Mostly they tell you which spreadsheet row to drop the model into.
What the speed number actually means
Gradium's post says Phonon 31m starts speaking in 7 ms on a laptop CPU. A benchmark writeup measured 6.9 ms to first audio on an M5. Those agree, which is rare enough to note.
But first audio is not the same as fast speech. What you feel in an app is time to first sound, then whether the stream keeps up after that.
The report that made me believe it came from a Reddit user on an i5-13600. They got roughly 6x real time on a P core and 3x on an E core, running Gradium's Docker container, with 30 to 40 ms to first audio.
That is a five year old desktop chip doing speech synthesis with no GPU and no network.
And the demo list is the tell. A Chrome extension that reads any page aloud. An Apple Watch guiding someone through a coffee brew with Wi-Fi switched off.
A dinosaur runner game where the dinosaur hosts a radio show from inside a browser tab. None of those work with a cloud call in the loop.
The licence is the actual story
Here is where i stopped being impressed and started being irritated.
Only one model is free for commercial use.
| Model | Size (q8) | Languages | Licence |
|---|---|---|---|
| Phonon 31m | 64 MB | EN | Apache 2.0 |
| Phonon 40m | 74.6 MB | EN, FR, DE, ES, PT | CC BY-NC |
| Phonon 40m multilingual | 74.6 MB | all five, one model | CC BY-NC |
The 40m is the one Gradium itself says to pick when expressivity and accuracy matter. It is the better model. It is also the one you cannot ship without a commercial agreement.
That split is defensible. Companies need revenue. But the release post leads with "open-sourcing Phonon" and the family framing hides a hard line.
A team that prototypes on the 40m because it sounds better, builds for a month, then reads the licence, has just lost a month.
One top commenter on the thread said it plainly: "CC BY NC means can't use it for work or to record voice for anything commercial."
The part that actually holds up
the problem isn't what you think. It is not quality. It is text normalization on ugly input.
TTS models fall apart on phone numbers, postal codes, version strings, temperatures. Gradium built a 500 sentence test set per language from the cases developers sent in, the ones their current models get wrong. Then they published it.
English word error rate on that hard set:
- Phonon 31m: 1.70%
- Phonon 40m multilingual: 2.11%
- Phonon 40m: 2.22%
- Kokoro: 3.50%
Kokoro is not a bad model. It is the model most side projects used last year. Phonon more than halving that error rate at half the size is the number that matters.
The demo clips make it concrete. Kokoro reads a delivery window as "nine point three to eleven point three." Phonon reads "9:30 to 11:30."
One of those is a bug report waiting to happen.
The small annoyances
what actually happens is that you notice the breathing.
One user said the voices were smooth but the respiration sounds were a bit much. Another found the duration_delta speed parameter only behaves between -0.5 and 0.2. Push past it and the end of the clip goes strange.
Those details never make the launch post. They are also the ones that decide whether you keep using something past day two.
And the release is actually a step down in size from what Gradium had in private beta. The earlier Phonon was around 100 million parameters. The public one is 31 and 40.
They went smaller on purpose, for footprint and speed.
i think that was the right call. It is also not what "frontier" usually means.
A short detour about names
Every AI product now has the same name as three other AI products.
There is Phonon the TTS model and Phonon the speech to text model. There is an Aurora in at least four product lines i could list. Nova, Pulse, Atlas, reused until the word stops meaning anything.
The joke on Reddit was that everyone is pulling names from the same out of date model. Probably true.
What gets me is that naming is the cheapest part of a launch. One afternoon and a domain search. And it decides whether your announcement thread is about your model or about someone else's.
Gradium shipped a result that took a research team a year. Then lost the first comment section to a name collision.
Who should skip this
If you are building a commercial multilingual voice product, skip Phonon 40m. The licence will stop you. Budget for a deal with Gradium, use the 31m English model, or use something else.
If you already pay for a hosted TTS API and your users are online, skip this too. Speech APIs are cheap now, and the ops work of shipping weights to devices is not.
If your product is a web app on a fast connection, skip it. A server call is fine.
The people who should care are the ones whose software cannot call a server. Offline apps. Field and medical tools.
Kids toys. Watch apps. Games.
Anything where the network is the enemy.
That is a smaller market than the launch thread implied.
The bit i keep coming back to
The 6.9 milliseconds is the number i can't shake.
Not because it is fast. Because it means a device with no internet, no GPU, and a five year old processor can now talk back in a voice that does not sound like a 2011 GPS unit.
Somewhere between the dinosaur radio host and the watch guiding a coffee pour, there is a product nobody has built yet.
i would bet on it being small and slightly weird. That is usually how this goes.
Top comments (0)