Show HN: Kitten TTS – 25MB CPU-Only, Open-Source TTS Model

Performance Results: Initial Latency: ~315ms for short text Audio Generation Speed (seconds of audio per second of processing): - Short text (12 chars): 3.35x realtime - Medium text (100 chars): 5.34x realtime - Long text (225 chars): 5.46x realtime - Very Long text (306 chars): 5.50x realtime Findings: - Model loads in ~710ms - Generates audio at ~5x realtime speed (excluding initial latency) - Performance is consistent across different voices (4.63x - 5.28x realtime)

Web version: https://clowerweb.github.io/kitten-tts-web-demo/

It sounds ok, but impressive for the size.

nine_k · 6 months ago

Does anybody find it funny that sci-fi movies have to heavily distort "robot voices" to make them sound "convincingly robotic"? A robotic, explicitly non-natural voice would be perfectly acceptable, and even desirable, in many situations. I don't expect a smart toaster to talk like a BBC host; it'd be enough is the speech if easy to recognize.

userbinator · 6 months ago

A robotic, explicitly non-natural voice would be perfectly acceptable, and even desirable, in many situations[...]it'd be enough is the speech if easy to recognize.

We've had formant synths for several decades, and they're perfectly understandable and require a tiny amount of computing power, but people tend not to want to listen to them:

https://en.wikipedia.org/wiki/Software_Automatic_Mouth

https://simulationcorner.net/index.php?page=sam (try it yourself to hear what it sounds like)

roywiggins · 6 months ago

This one is at least an interesting idea: https://genderlessvoice.com/

mfro · 6 months ago

In the Culture novels, Iain Banks imagines that we would become uncomfortable with the uncanny realism of transmitted voices / holograms, and intentionally include some level of distortion to indicate you're speaking to an image

incone123 · 6 months ago

Depends on the movie. Ash and Bishop in the Alien franchise sound human until there's a dramatic reason to sound more 'robotic'.

I agree with your wider point. I use Google TTS with Moon+Reader all the time (I tried audio books read by real humans but I prefer the consistency of TTS)

Twirrim · 6 months ago

> I don't expect a smart toaster to talk like a BBC host;

Well sure, the BBC have already established that it's supposed to sound like a brit doing an impersonation of an American: https://www.youtube.com/watch?v=LRq_SAuQDec

looperhacks · 6 months ago

I remember that the novelization of the fifth element describes that the cops are taught to speak as robotic as possible when using speakers for some reason. Always found the idea weird that someone would _want_ that

addandsubtract · 6 months ago

If you're on a Mac, you can type "say [thing to say]" into your terminal.

msgodel · 6 months ago

I personally prefer the older synthetic voices for TTS when the text is coming from software or a language model.

bkyan · 6 months ago

I got an error when I tried the demo with 6 sentences, but it worked great when I reduced the text to 3 sentences. Is the length limit due to the model or just a limitation for the demo?

divamgupta · 6 months ago

Currently we don't have chunking enabled yet. We will add it soon. That will remove the length limitations.

cess11 · 6 months ago

Perhaps a length limit? I tried this:

"This first Book proposes, first in brief, the whole Subject, Mans disobedience, and the loss thereupon of Paradise wherein he was plac't: Then touches the prime cause of his fall, the Serpent, or rather Satan in the Serpent; who revolting from God, and drawing to his side many Legions of Angels, was by the command of God driven out of Heaven with all his Crew into the great Deep."

It takes a while until it starts generating sound on my i7 cores but it kind of works.

This also works:

"blah. bleh. blih. bloh. blyh. bluh."

So I don't think it's a limit on punctuation. Voice quality is quite bad though, not as far from the old school C64 SAM (https://discordier.github.io/sam/) of the eighties as I expected.

Deleted Comment

Retr0id · 6 months ago

I tried to replicate their demo text but it doesn't sound as good for some reason.

If anyone else wants to try:

> Kitten TTS is an open-source series of tiny and expressive text-to-speech models for on-device applications. Our smallest model is less than 25 megabytes.

cortesoft · 6 months ago

Is the demo using the not smallest model?

quantummagic · 6 months ago

Doesn't work here. Backend module returns 404 :

https://clowerweb.github.io/node_modules/onnxruntime-web/dis...

Retr0id · 6 months ago

Looks like this commit 15 minutes ago broke it https://github.com/clowerweb/kitten-tts-web-demo/commit/6b5c...

(seems reverted now)

itake · 6 months ago

> Error generating speech: failed to call OrtRun(). ERROR_CODE: 2, ERROR_MESSAGE: Non-zero status code returned while running Expand node. Name:'/bert/Expand' Status Message: invalid expand shape

Doesn't seem to work with thai.

jainilprajapati · 6 months ago

You can also try on https://clowerweb.github.io/node_modules/onnxruntime-web/dis...

nxnsxnbx · 6 months ago

Thanks, I was looking for that. While the reddit demo sounds ok, even though on a level we reached a couple of years ago, all TTS samples I tried were barley understandable at all

divamgupta · 6 months ago

This is just an early checkpoint. We hope that the quality will improve in the future.

Aardwolf · 6 months ago

On PC it's a python dependency hell but someone managed to package it in self contained JS code that works offline once it loaded the model? How is that done?

a2128 · 6 months ago

ONNXRuntime makes it fairly easy, you just need to provide a path to the ONNX file, give it inputs in the correct format, and use the outputs. The ONNXRuntime library handles the rest. You can see this in the main.js file: https://github.com/clowerweb/kitten-tts-web-demo/blob/main/m...

Plus, Python software are dependency hell in general, while webpages have to be self-contained by their nature (thank god we no longer have Silverlight and Java applets...)

scotty79 · 6 months ago

It feels like it doesn't handle punctuation well. I don't hear sentence boundaries and commas. It sounds like continuous stream of words.

rohan_joshi · 6 months ago

yeah, this is just a preview model from an early checkpoint. the full model release will be next week which includes a 15M model and an 80M model, both of which will have much higher quality than this preview.

rldjbpin · 6 months ago

besides issues with webgpu (it is in beta fwiw), it'd be nice to increase voice speed through the setting without affecting the voice pitch.

Jotalea · 6 months ago

Using male voice 2 at 48kHz at 0.5x speed sounds a lot like Madeline's voice lines in Celeste. Seemed funny to me.

belchiorb · 6 months ago

This doesn’t seem to work on Safari. Works great on Chrome, though

divamgupta · 6 months ago

Hmm, we will look into it.

Dead Comment

  System Requirements
  Works literally everywhere

Haha, on one of my machines my python version is too old, and the package/dependencies don't want to install.

On another machie the python version is too new, and the package/dependencies don't want to install.

akx · 6 months ago

I opened a couple of PRs to fix this situation:

https://github.com/KittenML/KittenTTS/pull/21 https://github.com/KittenML/KittenTTS/pull/24 https://github.com/KittenML/KittenTTS/pull/25

If you have `uv` installed, you can try my merged ref that has all of these PRs (and #22, a fix for short generation being trimmed unnecessarily) with

    uvx --from git+https://github.com/akx/KittenTTS.git@pr-21-22-24-25 kittentts --output output.wav --text "This high quality TTS model works without a GPU"

tetris11 · 6 months ago

Thanks for the quick intro into UV, it looks like docker layers for python

I found the TTS a bit slow so I piped the output into ffplay with 1.2x speedup to make it sound a bit better

   uvx --from git+https://github.com/akx/KittenTTS.git@pr-21-22-24-25 kittentts --text "I serve 12 different beers at my restaurant for over 1000000 customers" --voice expr-voice-3-m --output - | ffplay -af "atempo=1.2" -f wav -

VagabundoP · 6 months ago

Install it with uvx that should solve the python issues.

https://docs.astral.sh/uv/guides/tools/

uv installation:

https://docs.astral.sh/uv/getting-started/installation/

IshKebab · 6 months ago

Yeah some people have a problem and think "I'll use Python". Now they have like fifty problems.

77pt77 · 6 months ago

I had the too new.

This package is the epitome of dependency hell.

Seriously, stick with piper-tts.

Easy to install, 50MB gives you excellent results and 100MB gives you good results with hundreds of voices.

xena · 6 months ago

It doesn't work on Fedora because of the lack of g++ having the right version.

trostaft · 6 months ago

Not sure if they've fixed between then and now, but I just had it working locally on Fedora.

  > g++ --version
  g++ (GCC) 15.1.1 20250521 (Red Hat 15.1.1-2)
  Copyright (C) 2025 Free Software Foundation, Inc.

divamgupta · 6 months ago

We are working to fix that. Thanks

pjc50 · 6 months ago

"Fixing python packaging" is somewhat harder than AGI.

raybb · 6 months ago

Have you considered offering a uvx command to run to get people going quickly?

flanked-evergl · 6 months ago

Just point people to uv/uvx.

hahn-kev · 6 months ago

Python man

baobun · 6 months ago

    man python

There you go.

turnsout · 6 months ago

You're getting a lot of comments along the lines of "Why don't you just ____," which only shows how Stockholmed the entire Python community is.

With no other language are you expected to maintain several entirely different versions of the language, each of which is a relatively large installation. Can you imagine if we all had five different llvms or gccs just to compile five different modern C projects?

I'm going to get downvoted to oblivion, but it doesn't change the reality that Python in 2025 is unnecessarily fragile.

jhurliman · 6 months ago

That’s exactly what I have. The C++ codebases I work on build against a specific pinned version of LLVM with many warnings (as errors) enabled, and building with a different version entails a nonzero amount of effort. Ubuntu will happily install several versions of LLVM side by side or compilation can be done in a Docker container with the correct compiler. Similarly, the TypeScript codebases I work with test against specific versions of node.js in CI and the engine field in package.json is specified. The different versions are managed via nvm. Python is the same via uv and pyproject.yaml.

debugnik · 6 months ago

I agree with your point, but

> if we all had five different llvms or gccs

Oof, those are poor examples. Most compilers using LLVM other than clang do ship with their own LLVM patches, and cross-compiling with GCC does require installing a toolchain for each target.

77pt77 · 6 months ago

> Can you imagine if we all had five different llvms or gccs just to compile five different modern C projects?

Yes, because all I have to do is look at the real world.

sigmoid10 · 6 months ago

There are still people who use machine wide python installs instead of environments? Python dependency hell was already bad years ago, but today it's completely impractical to do it this way. Even on raspberries.

superkuh · 6 months ago

Yep. Python stopped being Python a decade ago. Now there are just innumberable Pythons. Perl... on the otherhand, you can still run any perl script from any time on any system perl interpreter and it works! Granted, perl is unpopular and not getting constant new features re: hardcore math/computation libs.

Anyway, I think I'll stick with Festival 1.96 for TTS. It's super fast even on my core2duo and I have exactly zero chance of getting this Python 3'ish script to run on any machine with an OS older than a handful of years.

lynx97 · 6 months ago

Debian pretty much "solved" this by making pip refuse to install packages if you are not in an venv.

yjftsjthsd-h · 6 months ago

Using venv won't save you from having the wrong version of the actual Python interpreter installed.

dzogchen · 6 months ago

Such an ignorant thing to say for something that requires 25MB RAM.

Bilal_io · 6 months ago

Not sure what the size has to do with anything.

I send you a 500kb Windows .exe file and claim it runs literally everywhere.

Would it be ignorant to say anything against it because of its size?

dlcarrier · 6 months ago

It reminds me of the costs and benefits of RollerCoaster Tycoon being written in assembly language. Because it was so light on resources, it could run on any privately owned computer, or at least anything x86, which was pretty much everything at the time.

Now, RISC architectures are much more common, so instead of the rare 68K Apple/Amiga/etc computer that existed at the time, it's super common to want to run software on an ARM or occasionally RISC-V processor, so writing in x86 assembly language would require emulation, making for worse performance than a compiled language.

exe34 · 6 months ago

system python is for system applications that are known to work together. If you need a python install for something else, there's venv or conda and then pip install stuff.

Dead Comment

miellaby · 6 months ago

You're supposed to use venv for everything but the python scripts distributed with your os

mlboss · 6 months ago

Reddit post with generated audio sample: https://www.reddit.com/r/LocalLLaMA/comments/1mhyzp7/kitten_...

seligman99 · 6 months ago

And a quick video with all of the different voices:

https://www.youtube.com/watch?v=60Dy3zKBGQg

a96 · 6 months ago

Thanks. I really would not want to listen to any of these regularly.

tracker1 · 6 months ago

Cool, thanks... aside: the last male voice sounds high/drunk.

Eduard · 6 months ago

thank you!

smusamashah · 6 months ago

The reddit video is awesome. I don't understand how people are calling it an OK model. Under 25MB and cpu only for this quality is amazing.

soasme · 6 months ago

Just made a TTS tool based on Kitten TTS, fully browser based, no Python server backend: https://quickeditvideo.com/tts/ A tts model of this size should be industry standard!

The people calling it "OK" probably tried it for themselves. Whatever model is being demoed in that video is not the same as the 25MB model they released.

sergiotapia · 6 months ago

https://vocaroo.com/1njz1UwwVHCF

It doesn't sound so good. Excellent technical achievement and it may just improve more and more! But for now I can't use it for consumer facing applications.

Zardoz84 · 6 months ago

Sounds very clear. For a non native english speaker like me, it's easy to understand.

tapper · 6 months ago

Sounds slow and like something from an anine

ricardobeat · 6 months ago

Speech speed is always a tunable parameter and not something intrinsic to the model.

The comparison to make is expressiveness and correct intonation for long sentences vs something like espeak. It actually sounds amazing for the size. The closest thing is probably KokoroTTS at 82M params and ~300MB.

numpad0 · 6 months ago

The only real questions are which Chinese gacha game they ripped data from and whether they used Claude Code or Gemini CLI for Python code. I bet one can get a formant match from output this much overfit to whatever data. This isn't going to stay up for long.

KaiserPro · 6 months ago

was it cross trained on futurama voices?

junon · 6 months ago

That would be a feature!

archon810 · 6 months ago

Sounds like Mort from Family Guy.

It was not

Aachen · 6 months ago

Impressive technical achievement, but in terms of whether I'd use it: oof, that male voice is like one of these fake-excited newsreaders. Like they're always at the edge of their breath. The female one is better but still someone reading out an advertisement for a product they were told they must act extra excited for. I assume this is what the majority of training data was like and not an intentional setting for the demo. Unsure whether I could get used to that

I use TTS on my phone regularly and recently also tried this new project on F-Droid called SherpaTTS, which grabs some models from Huggingface. They're super heavy (the phone suspends other apps to disk while this runs) and sound good, but in the first news article there were already one or two mispronunciations because it's guessing how to say uncommon or new words and it's not based on logical rules anymore to turn text into speech

Google and Samsung have each a TTS engine pre-installed on my device and those sound and work fine. A tad monotonous but it seems to always pronounce things the same way so you can always work out what the text said

Espeak (or -ng) is the absolute worst, but after 30 seconds of listening closely you get used to it and can understand everything fine. I don't know if it's the best open source option (probably there are others that I should be trying) but it's at least the most reliable where you'll always get what is happening and you can install it on any device without licensing issues

willwade · 6 months ago

anyone else wants to try sherpaOnnx you can try this.. https://github.com/willwade/tts-wrapper we recently added in the kokoro models which should sound a lot better. There are a LOT of models to choose from. I have a feeling the Droid app isnt handling cold starts very well.

Thanks a lot for the detailed feedback. We are working on some models which do not use a phonemizer

bornfreddy · 6 months ago

RHvoice is pretty good, imho.

I hope this is the future. Offline, small ML models, running inference on ubiquitous, inexpensive hardware. Models that are easy to integrate into other things, into devices and apps, and even to drive from other models maybe.

WhyNotHugo · 6 months ago

Dedicated single-purpose hardware with models would be even less energy-intensive. It's theoretically possible to design chips which run neural networks and alike using just resistors (rather than transistors).

Such hardware is not general-purpose, and upgrading the model would not be possible, but there's plenty of use-cases where this is reasonable.

amelius · 6 months ago

But resistors are, even in theory, heat dissipating devices. Unlike transistors, which can in theory be perfectly on or off (in both cases not dissipating heat).

regularfry · 6 months ago

It's theoretically possible but physical "neurons" is a terrible idea. The number of connections between two layers of an FF net is the product of the number of weights in each, so routing makes every other problem a rounding error.

The thing is that the new models keep coming every day. So it’s economically not feasible to make chips for a single model

theshrike79 · 6 months ago

This is what Apple is envisioning with their SLMs, like having a model specifically for managing calendar events. It doesn't need to have the full knowledge of all humanity in it - just what it needs to manage the calendar.

koolala · 6 months ago

Issue is their envisioning everyone only using Apple products.

throwaway28733 · 6 months ago

Apple's hardware is notoriously overpriced, so I don't think they're envisioning that at all.

discardedrefuse · 6 months ago

Hmm. A pay once (or not at all) model that can run on anything? Or a subscription model that locks you in, and requires hardware that only the richest megacorps can afford? I wonder which one will win out.

The popular one.

That is our vision too!

This is our goal too.

yeah totally. the quality of these tiny models are only going to go up.

peanut_merchant · 6 months ago

I ran some quick benchmarks.

Ubuntu 24, Razer Blade 16, Intel Core i9-14900HX

Thanks for running the benchmarks. Currently the models are not optimized yet. We will optimize loading etc when we release an SDK meant for production :)

don-bright · 6 months ago

on my Intel(R) Celeron(R) N4020 CPU @ 1.10GHz it takes 6 seconds to import/load and text generation is roughly 1x realtime on various lengths of text.

thanks for testing on the same hardware as mine, before me.

blopker · 6 months ago

MutedEstate45 · 6 months ago

The headline feature isn’t the 25 MB footprint alone. It’s that KittenTTS is Apache-2.0. That combo means you can embed a fully offline voice in Pi Zero-class hardware or even battery-powered toys without worrying about GPUs, cloud calls, or restrictive licenses. In one stroke it turns voice everywhere from a hardware/licensing problem into a packaging problem. Quality tweaks can come later; unlocking that deployment tier is the real game-changer.

yeah, we are super excited to build tiny ai models that are super high quality. local voice interfaces are inevitable and we want to power those in the future. btw, this model is just a preview, and the full release next week will be of much higher quality, along w another ~80M model ;)

woadwarrior01 · 6 months ago

> It’s that KittenTTS is Apache-2.0

Have you seen the code[1] in the repo? It uses phonemizer[2] which is GPL-3.0 licensed. In its current state, it's effectively GPL licensed.

[1]: https://github.com/KittenML/KittenTTS/blob/main/kittentts/on...

[2]: https://github.com/bootphon/phonemizer

Edit: It looks like I replied to an LLM generated comment.

oezi · 6 months ago

The issue is even bigger: phonemizer is using espeak-ng, which isn't very good at turning graphemes into phonemes. In other TTS which rely on phonemes (e.g. Zonos) it turned out to be one of the key issues which cause bad generations.

And it isn't something you can fix, because the model was trained on bad phonemes (everyone uses Whisper + then phonemizes the text transcript).

jacereda · 6 months ago

https://github.com/KittenML/KittenTTS/issues/17

gorgoiler · 6 months ago

This would only apply if they were distributing the GPL licensed code alongside their own code.

If my MIT-licensed one-line Python library has this line of code…

  run([“bash”, “-c”, “echo hello”])

…I’m not suddenly subject to bash’s licensing. For anyone wanting to run my stuff though, they’re going to need to make sure they themselves have bash installed.

(But, to argue against my own point, if an OS vendor ships my library alongside a copy of bash, do they have to now relicense my library as GPL?)

Hackbraten · 6 months ago

Given that the FSF considers Apache-2.0 to be compatible with GPL-3.0 [0], how could the fact that phonemizer is GPL-3.0 possibly be an issue?

[0]: https://www.gnu.org/licenses/license-list.html#apache2

keyKeeper · 6 months ago

Okay, what's stopping you from feeding the code into an LLM and re-write it and make it yours? You can even add extra steps like make it analyze the code block by block then supervise it as it is rewriting it. Bam. AI age IP freedom.

Morals may stop you but other than that? IMHO all open source code is public domain code if anyone is willing to spend some AI tokens.

defanor · 6 months ago

A Festival's English model, festvox-kallpc16k, is about 6 MB, and it is a large model; festvox-kallpc8k is about 3.5 MB.

eSpeak NG's data files take about 12 MB (multi-lingual).

I guess this one may generate more natural-sounding speech, but older or lower-end computers were capable of decent speech synthesis previously as well.

Joel_Mckay · 6 months ago

Custom voices could be added, but the speed was more important to some users.

$ ls -lh /usr/bin/flite

Listed as 27K last I checked.

I recall some Blind users were able to decode Gordon 8-bit dialogue at speeds most people found incomprehensible. =3

> KittenTTS is Apache-2.0

What about the training data? Is everyone 100% confident that models are not a derived work of the training inputs now, even if they can reproduce input exactly?

entropie · 6 months ago

I play around with a nvidia jetson orin nano super right now and its actually pretty usuable with gemma3:4b and quite fast - even image processing is done in like 10-20 seconds but this is with GPU support. When something is not working and ollama is not using the GPU this calls take ages because the cpu is just bad.

Iam curious how fast this is with CPU only.

phh · 6 months ago

It depends on espeak-ng which is GPLv3

ethan_smith · 6 months ago

This opens up voice interfaces for medical devices, offline language learning tools, and accessibility gadgets for the visually impaired - all markets where cloud dependency and proprietary licenses were showstoppers.

Narishma · 6 months ago

But Pi Zero has a GPU, so why not make use of it?

Because then you're stuck on that device only.

CyberDildonics · 6 months ago

The github just has a few KB of python that looks like an install script. How is this used from C++ ?

antisol · 6 months ago

klipklop · 6 months ago

I tried it. Not bad for the size (of the model) and speed. Once you install all the massive number of libraries and things needed we are a far cry away from 25MB though. Cool project nonetheless.

devnen · 6 months ago

That's a great point about the dependencies.

To make the setup easier and add a few features people are asking for here (like GPU support and long text handling), I built a self-hosted server for this model: https://github.com/devnen/Kitten-TTS-Server

The goal was a setup that "just works" using a standard Python virtual environment to avoid dependency conflicts.

The setup is just the standard git clone, pip install in a venv, and python server.py.

k4rnaj1k · 6 months ago

Oh wow, really impressive. How long did this take you to make?

Dayshine · 6 months ago

It mentions ONNX, so I imagine an ONNX model is or will be available.

ONNX runtime is a single library, with C#'s package being ~115MB compressed.

Not tiny, but usually only a few lines to actually run and only a single dependency.

wongarsu · 6 months ago

The repository already runs an ONNX model. But the onnx model doesn't get English text as input, it gets tokenized phonemes. The prepocessing for that is where most of the dependencies come from.

Which is completely reasonable imho, but obviously comes with tradeoffs.

We will try to get rid of dependencies.

Usually pulling in lots of libraries helps develop/iterate faster. Then can be removed later once the whole thing starts to take shape.

zelphirkalt · 6 months ago

This case might be different, but ... usually that "later" never happens.

keyle · 6 months ago

I don't mind so much the size in MB, the fact that it's pure CPU and the quality, what I do mind however is the latency. I hope it's fast.

Aside: Are there any models for understanding voice to text, fully offline, without training?

I will be very impressed when we will be able to have a conversation with an AI at a natural rate and not "probe, space, response"

Nvidia's parakeet https://huggingface.co/nvidia/parakeet-tdt-0.6b-v2 appears to be state of the art for english: 10x faster than Whisper.

My mid-range AMD CPU is multiple times faster than realtime with parakeet.

colechristensen · 6 months ago

>Aside: Are there any models for understanding voice to text, fully offline, without training?

OpenAI's whisper is a few years old and pretty solid.

https://github.com/openai/whisper

Whisper tends to fill silence with random garbage from its training set. [0] [1] [2]

[0]: https://github.com/openai/whisper/discussions/679 [1]: https://github.com/openai/whisper/discussions/928 [2]: https://github.com/openai/whisper/discussions/2608

jiehong · 6 months ago

Voice to text fully offline can be done with whisper. A few apps offer it for dictation or transcription.

blensor · 6 months ago

"The brown fox jumps over the lazy dog.."

Average duration per generation: 1.28 seconds

Characters processed per second: 30.35

"Um"

Average duration per generation: 0.22 seconds

Characters processed per second: 9.23

"The brown fox jumps over the lazy dog.. The brown fox jumps over the lazy dog.."

Average duration per generation: 2.25 seconds

Characters processed per second: 35.04

processor : 0

vendor_id : AuthenticAMD

cpu family : 25

model : 80

model name : AMD Ryzen 7 5800H with Radeon Graphics

stepping : 0

microcode : 0xa50000c

cpu MHz : 1397.397

cache size : 512 KB

moffkalast · 6 months ago

Hmm that actually seems extremely slow, Piper can crank out a sentence almost instantly on a Pi 4 which is a like a sloth compared to that Ryzen and the speech quality seems about the same at first glance.

I suppose it would make sense if you want to include it on top of an LLM that's already occupying most of a GPU and this could run in the limited VRAM that's left.

assuming most answers will be more than a sentence, 2.25 seconds is already long enough if you factor the token generation in between... and imagine with reasoning!... We're not there yet.

Teever · 6 months ago

Any idea what factors play into latency in TTS models?

Mostly model size, and input size. Some models which use attention are O(N^2)