Local, CPU-Friendly, High-Quality TTS (Text-to-Speech) with Kokoro

I was kind of waiting for Apple to ship something like this and using speechify in the meantime, so I was pleasantly surprised to stumble across Kokoro in a thread on HN a few days ago. The voices are better than the cloud provider IMO.

I'm using it in an open source tool I built for listening to coding agents instead of watching them work, and it's been great. Local, private, free to run, and enough voices that I can actually use a different one for each agent.

Wrote a bit more about the project here: https://jonmagic.com/posts/i-stopped-watching-my-agents-work...

I have used Kokoro fairly extensively for an accessibility product. I have loved working with it (especially because I don't have an NVidia GPU like many TTS of similar quality require).

I particularly appreciate the fact that it lets you manually add IPA pronunciation guides. There have been some cases where an important word is a homograph and Kokoro assumed the wrong pronunciation.

The place where it falls a little short is in saying just a single word or two. Try having it say simply "six" and it almost always says something like "ah-six-ah". I found a way around that though. If you give it a longer sentence to say (eg "The word is: six") it will say it fine. The trick is that the Kokoro API gives you the timestamp of each word in the sentence. So you can have a Python script crop out just the word you care about. The intonation is a little flat this way, but is very reliable.

I asked about this on the discord, and was told that it is a limitation of the small parameter size. But in fairness to Kokoro, even eleven-labs' voices suffer from this occasionally.

Fun... This is something I actually care about...

I used to keep a version of whisperx around, because I think it's important to have not just transcription, but also timing and speaker identification (e.g. for subtitles)... It depends on pyannote, though, which has some wierd licensing (and is tougher to script the installs because of it), so I wanted to look at something that both had better transcription, and supported diarization (the speaker and timing). I decided on parakeet for the transcription with softformer (the diarization), but most of the available engines for it don't include softformer.

I coded up an OpenAI compatible server for parakeet-rs ( https://github.com/altunenes/parakeet-rs ) (which does support softformer) and I've been using it with OpenWhispr (a desktop app for transcription that handles all sorts of neat thing).

I'm doing CPU-only transcription (because I use my GPUs for other stuff and haven't gotten around to adding in the GPU-path), but it's incredibly empowering to be able to have local transcriptions at will.

Love this model. I’m GPU poor and have had FOMO that I haven’t played with local models at all. About a month ago I setup Kokoro on my GTX1650 to do TTS for an article reader. A simple WebUI lets me paste a URL or a chunk of copy pasted text. Python cleans it up and sends to Kokoro for TTS and it’s then served via RSS for Apple Podcasts. Then for my morning drive I’ll catch up on articles or blog posts I’ve gathered.

At some point I’d like to play with separate voices and see if I could build something like NotebookLM for kind of like a radio morning show of news items I’ve gathered.

A couple months back I wrote a chrome extension that does this on any webpage, with simultaneous highlighting of the sentence being read. Skips both the container launching step and the copy pasting website contents step. Might be useful to anyone trying to use kokoro ergonomically.

https://chromewebstore.google.com/detail/local-reader-ai-on-...

This repo is a good starting point for comparing TTS models https://github.com/5uck1ess/tts-bench

Kokoro is a really good model, considered it’s released 1.5 years ago. It’s punching above its weight https://5uck1ess.github.io/tts-bench/scores.html

TTS has come incredible long way, there are so many options. There is Kokoro of course, then there is Pocket TTS which is also a tiny 100M model that allows voice cloning. There is also Chatterbox Turbo, which is bit bigger but also allows for more emotional control of the voice. And then finally there is the Fish Audio S2, which is even bigger but allows even larger and essentially unbounded finegrained control of tone and emotion. And all of these can easily run on your Macbook.

Super cool!!

I've been using my own solution since January. I'm on Linux, and can't use Aqua, Whipsrflow etc... So i made my own.

Recently cleaned it up and made it install friendly.

If anyone is interested, you can check it out here: https://github.com/Hugo0/voiceio

It's self-improving over time, runs on your local machine, and is generally decent software. 60% of my interaction with my PC nowadays is pure voice input.

This is awesome. People are already talking about use of local models for heavy tasks like llm inference. TTS is very much possible on device without any high end gpu. That's why Ive been working integrating it into a free reader web app with some features more than just getting audio from a text.

https://desktop.with.audio/reader

I spent a day fiddling with AI and dropping the expensive layers in kokoro, on phones, on CPU, on MNN, it runs 3x faster.

Quality is very close.

Will vary in your setup, but here is my script: https://github.com/DavidVentura/translator-rs/blob/master/sc...

I don't want to mess with port numbers and gpu cards; I just want an upgrade from the age-old:

    apt install festival

I'm using Kokoro for a fun little side-project browser-based game I'm working on. It's legitimately super good for being only 85mb (for the wasm version) or 300mb (for the webgpu version).

I recently created a video and didn't want to use my voice on it.

Rather than TTS I did STS (speech to speech) through Eleven Labs (you upload the video it alters the audio track to voice of choosing with some parameters you can control).

I showed it to a bunch of people and they could not believe it was non-human. The bit that got most was all the pausing, broken sentences ...essentially elements you don't put into text if your doing T2S.

An LLM over the original text could perhaps inject these elements though if prompted correctly.

Cool I actually got it ported to iPhone’s ANE finally yesterday! So we can get both rt natural local TTS and 4x less battery drainage and thermals

I'm using exactly this TTS engine for my intercom door system I built. The quality of the TTS is very good.

Supertonic 3 is pretty amazing too. I’ve got time to first sound down to well under a second by streaming chunks and stitching together from CPU with goonx (non c-go onnx) - happy to upload model if any go devs interested.

kokoro is decent but pocket-tts is much better especially when you rip a good voice. https://github.com/kyutai-labs/pocket-tts

the onnx version of pocket-tts does perform better. https://huggingface.co/KevinAHM/pocket-tts-onnx

I love Kokoro. I use it to read ebooks that don't have audiobooks and it works pretty good for that. I have a Python script that reads epub/html, runs the model and writes mp3s.

Kokoro supports a limited number of languages. I've had to resort to other models to support Dutch, and they just aren't as good. And usually a lot slower and bigger (too big for my 8GB VRAM). I've had to resort to the Windows built-in TTS. It doesn't sound natural at all, but at least it can pronounce most words and is very fast.

I built a pipeline through hermes using edge-tts to automate and listen to links that I provide to it just this morning, google notebooklm style. I replaced the TTS model with Kokoro after seeing this post, thank you. Here's the pipeline if anyone is interested. https://www.klaweht.com/2026-07-07-link-to-podcast-rss-pipel... By the way, it took hermes just around 10-15 minutes to build first iteration. I am impressed.

I am entirely sold on Qwen3-TTS's voice cloning. It runs locally and I can run it as many times as I want.

Saw it first on reddit, and later I created a small project to generate audio books from epub. So far I've listened to couple of books generated this way and am quite satisfied with the quality. There is just one particular word I remember that it pronounced wrongly - "Malay".

Love Kokoro tts. I wrote https://github.com/Jud/kokoro-coreml to try pushing the limits a bit on speed & size. Such great quality at a given size. As others have mentioned short utterances are problematic, but solvable.

Kokoro is great. I built an mcp for it a while back that has gotten decent traction - https://github.com/mberg/kokoro-tts-mcp if anyone wants to go that route

Any good debian-ish distros that integrate TTS and STT in a usable shell?

Both Text-to-Speech and Speech-to-Text now have local models that are good enough to get the job done. Kokoro for TTS, Parakeet for STT and Fluid-1 for text formatting (I use it with FluidVoice). I hope this is a trend that continues for other applications.

It's interesting that the male voices are all so much worse than the female voices (several are quite good). There is bias in machine learning, but I wonder whether there is also systematically more training data of female speech?

Naive question, but I once downloaded a particular voice file that I wanted to use with some other RVC TTS project, but ended up not being able to run it CPU only, so I only kept the voice I wanted. Thing is, the voice is in .pth format, and on Kokoro's huggingface page, their voices are all .pt.

Would I be able to use this voice I already have with Kokoro? If not, is there any way to convert it? I could always go looking if someone made this specific voice but in .pt format, but I barely mess with AI and don't know how I could search for this.

Off-topic, re: “kokoro”

Article refers to: https://huggingface.co/hexgrad/Kokoro-82M

Caught my eye for the related name to my book of Kakuro puzzles for sale at https://www.kakurokokoro.com

Kokoro comes from the Japanese word meaning something like heart or spirit, and not the literal ones.

I use kokoro with home assistant and its great. I find its the most natural sounding and small too.

I speak over sonos speakers when certain events happen. And use it as my voice assistant.

https://wlejon.github.io/kokoro-lab-web/

You can tweak the pitch as well.

This is Amazing and a game changer. Millions were spent during NLP era to achieve even <50% what this model offers.

Now this on a CPU is next level. When algorithms perform well on commodity hardware, the scale tips.

This gives hope that CPULLM's are not far off that'll be just fine for majority of use cases.

Who is going to hack together a mac widget that allows us to select text anywhere, press a shortcut key and finally get a non robotic voice outputted in a reasonable amount of time?

I am aware of the Option + Esc shortcut on osx for the onboard TTS but wow is it hard to listen to in 2026.

this is very cool! i also made a kokoro based tts tool which runs on a jetson orin kit. it serves tts generations over durable streams, try it out here: https://streamtts.dev/ , i also wrote about it: https://s2.dev/blog/local-ai

kokoro is surprisingly great at nuance but it's tough to improve that last ~2% or so. kokoro + rvc is really great too; i use that for ELEMENT47, the LLM-centric comedy podcast i do that i wish more people would listen to. (e47.net , feel free to subscribe!)

When I hear the male voice I think: "Ok, it's the Youtube guy".

https://github.com/rhulha/StreamingKokoroJS all in browser, 100% private, nothing tracked

I've used Piper for local TTS before, and Kokoro looks like an interesting

Anyone know which local TTS is best, close to Eleven Labs quality?

Another endorsement - I used Kokoro pretty extensively with an app I was developing over the last year and it's been excellent, both on- and off- GPU. Even with Elevenlabs (long time subscriber) the comparative quality of Kokoro keeps up really well until you get to their larger models with their professional voices.

I do wish there were better support for SSML, as well as deeper documentation of how to influence inflection in-line, but the default does well with standard emphasis (e.g. putting asterisks around text elements). Both asks are getting outside the zone of reasonable asks for this sort of distribution, though, and I remain incredibly grateful for the quality of what hexgrad and nazdridoy have put out in the world.

I just hooked it up to my personal AI Japanese Teacher app, pretty good quality / natural sounding speech in mixed English / Japanese while running fast on CPU so I don't waste VRAM.

kokoro is very nice, but I am disappointed that this wasn't an announcement of a new kokoro version.

I don't want to just spew AI-hate, but is an LLM actually necessary for this? I haven't worked with, but came across loads of non-AI TTS tools. Are these now exceptionally better to justify the overhead? Genuinely asking.

Has anyone tested/ported Kokoro To mobile?

I agree that Kokoro is a good TTS model.

If you're interested in an ONNX version and a permissively licensed TTS Tokenizer, I built a pipeline for that a while back: https://huggingface.co/NeuML/kokoro-base-onnx

On macOS I've been using piper (https://github.com/OHF-Voice/piper1-gpl) to announce claude code notifications and it works perfectly!

> Apple M2 Pro: 4.5 seconds

> AMD Ryzen 7 8745HS: 1.5 seconds

These two can probably do it much faster on their iGPUs.

curious to know if it comes with audio tags?

It crashes as soon as you put a little paragraph of text on Apple M2 Pro.

Hard pass.

Why do these half baked projects get all the attention and thousands of clicks when it just takes a simple thing to bring the whole castle down?

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Yeah, we need to keep up with how quickly AI types back to us, typing on the keyboards is no longer quick enough, gotta dictate everything now.