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KittenML
KittenTTS
Python2025–2026
KittenML / KittenTTS

KittenTTS

Open-source State-of-the-art TTS model which runs on a CPU 😻

AI & Machine Learning
Explore on GitHubRead Hacker News discussions
13Distinct people
15Mentions
0Explicit recommenders
16.9KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Open-source State-of-the-art TTS model which runs on a CPU 😻

GitHub

Where it is used

No documented product use was verified in the last source check.

What people are saying

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Also in these discussions

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This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by month15 dated mentions

Observed mentions: 2025-08-05 13:30:10 UTC to 2026-03-19 23:33:27 UTC.

02468102025-08-01 00:00:00 UTC to 2025-09-01 00:00:00 UTC (exclusive): 10 mentions; 2 submissions, 8 commentsAug 20252025-09-01 00:00:00 UTC to 2025-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-10-01 00:00:00 UTC to 2025-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-11-01 00:00:00 UTC to 2025-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsNov 20252025-12-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-01-01 00:00:00 UTC to 2026-02-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2026-02-01 00:00:00 UTC to 2026-03-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2026-03-01 00:00:00 UTC to 2026-04-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 commentsMar 2026

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Aug 20252025-08-01 00:00:00 UTC2025-09-01 00:00:00 UTC1028
Sep 20252025-09-01 00:00:00 UTC2025-10-01 00:00:00 UTC000
Oct 20252025-10-01 00:00:00 UTC2025-11-01 00:00:00 UTC000
Nov 20252025-11-01 00:00:00 UTC2025-12-01 00:00:00 UTC000
Dec 20252025-12-01 00:00:00 UTC2026-01-01 00:00:00 UTC000
Jan 20262026-01-01 00:00:00 UTC2026-02-01 00:00:00 UTC202
Feb 20262026-02-01 00:00:00 UTC2026-03-01 00:00:00 UTC101
Mar 20262026-03-01 00:00:00 UTC2026-04-01 00:00:00 UTC211

What Hacker News says

15 sources
tredre3·Mar 19, 2026
This is something I've been looking for (the <50MB models in particular). Unfortunately my feedback is as follows: Downloading https://github.com/KittenML/KittenTTS/releases/download/0.8.1/kittentts-0.8.1-py3-… (22 kB) Collecting num2words (from kittentts==0.8.1) Using cached num2words-0.5.14-py3-none-any.whl.metadata (13 kB) Collecting spacy (from kittentts==0.8.1) Using cached spacy-3.8.11-cp314-cp314-win_amd64.whl.metadata (28 kB) Collecting espeakng_loader (from kittentts==0.8.1) Using cached espeakng_loader-0.2.4-py3-none-win_amd64.whl.metadata (1.3 kB) INFO: pip is looking at multiple versions of kittentts to determine which version is compatible with other requirements. This could take a while. ERROR: Ignored the following versions that require a different python version: 0.7.1
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0 Requires-Python >=3.8,<3.13; 0.7.11 Requires-Python >=3.8,<3.13; 0.7.12 Requires-Python >=3.8,<3.13; 0.7.13 Requires-Python >=3.8,<3.13; 0.7.14 Requires-Python >=3.8,<3.13; 0.7.15 Requires-Python >=3.8,<3.13; 0.7.16 Requires-Python >=3.8,<3.13; 0.7.17 Requires-Python >=3.8,<3.13; 0.7.5 Requires-Python >=3.8,<3.13; 0.7.6 Requires-Python >=3.8,<3.13; 0.7.7 Requires-Python >=3.8,<3.13; 0.7.8 Requires-Python >=3.8,<3.13; 0.7.9 Requires-Python >=3.8,<3.13; 0.8.0 Requires-Python >=3.8,<3.13; 0.8.1 Requires-Python >=3.8,<3.13; 0.8.2 Requires-Python >=3.8,<3.13; 0.8.3 Requires-Python >=3.8,<3.13; 0.8.4 Requires-Python >=3.8,<3.13; 0.9.0 Requires-Python >=3.8,<3.13; 0.9.2 Requires-Python >=3.8,<3.13; 0.9.3 Requires-Python >=3.8,<3.13; 0.9.4 Requires-Python >=3.8,<3.13; 3.8.3 Requires-Python >=3.9,<3.13; 3.8.5 Requires-Python >=3.9,<3.13; 3.8.6 Requires-Python >=3.9,<3.13; 3.8.7 Requires-Python >=3.9,<3.14; 3.8.8 Requires-Python >=3.9,<3.14; 3.8.9 Requires-Python >=3.9,<3.14 ERROR: Could not find a version that satisfies the requirement misaki>=0.9.4 (from kittentts) (from versions: 0.1.0, 0.3.0, 0.3.5, 0.3.9, 0.4.0, 0.4.4, 0.4.5, 0.4.6, 0.4.7, 0.4.8, 0.4.9, 0.5.0, 0.5.1, 0.5.2, 0.5.3, 0.5.4, 0.5.5, 0.5.6, 0.5.7, 0.5.8, 0.5.9, 0.6.0, 0.6.1, 0.6.2, 0.6.3, 0.6.4, 0.6.5, 0.6.6, 0.6.7, 0.7.0, 0.7.1, 0.7.2, 0.7.3, 0.7.4) ERROR: No matching distribution found for misaki>=0.9.4 I realize that I can run a multiple versions of python on my system, and use venv to managed them (or whatever equivalent is now trendy), but as I near retirement age all those deep dependencies nets required by modern software is really depressing me. Have you ever tried to build a node app that hasn't been updated in 18 months? It can't be done. Old man yelling at cloud I guess shrugs.
In Show HN: Three new Kitten TTS models – smallest less than 25MB
rohan_joshi·Mar 19, 2026Submission

Show HN: Three new Kitten TTS models – smallest less than 25MB

Kitten TTS (https://github.com/KittenML/KittenTTS) is an open-source series of tiny and expressive text-to-speech models for on-device applications. We had a thread last year here: https://news.ycombinator.com/item?id=44807868. Today we're releasing three new models with 80M, 40M and 14M parameters. The largest model (80M) has the highest quality. The 14M variant reaches new SOTA in expressivity among similar sized models, despite being <25MB in size. This release is a major upgrade from the previous one and supports English text-to-speech applications in eight voices: four male and four female. Here's a short demo: https://www.youtube.com/watch?v=ge3u5qblqZA. Most models are quantized to int8 + fp16, and they use ONNX for runtime. Our models are designed to run anywhere eg. raspberry pi, low-end smartphones, wearables, browsers etc. No G
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PU required! This release aims to bridge the gap between on-device and cloud models for tts applications. Multi-lingual model release is coming soon. On-device AI is bottlenecked by one thing: a lack of tiny models that actually perform. Our goal is to open-source more models to run production-ready voice agents and apps entirely on-device. We would love your feedback!
561 points · Open discussion
rohan_joshi·Feb 20, 2026
New Kitten TTS V0.8 models are out in three variants - 80M, 40M, 14M. The largest model has the highest quality. The 14M variant reaches new SOTA in expressivity among similar sized models, despite being <25MB in size. All models are highly expressive and realistic with high quality voices. Kitten TTS is an open-source series of tiny and expressive text-to-speech models for on-device applications, built by KittenML (with < 3) . This release supports English text-to-speech applications in eight voices: four male and four female. Most models are quantized to int8 + fp16, and it uses onnx for runtime. The model is designed to run literally anywhere eg. raspberry pi, low-end smartphones, wearables, browsers etc. No GPU required! This release bridges the gap between on-device and cloud models for tts applications. Multi-lingual support is p
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lanned for the future. We'd love your feedback! On-device AI is currently bottlenecked by the availability of tiny performant models. We're trying to change that by releasing open-source models that can unlock on-device voice agents and applications in the next few months. Code, weights and more information available on our github: https://github.com/KittenML/KittenTTS
In Show HN: Three new models by KittenML. <25 MB Open-source TTS. Highly Expressive
soulofmischief·Jan 24, 2026
I have a great local assistant that works end-to-end with voice. It's built on local, web-first technologies, it fits small LLMs in memory and manages inference and TTS/STT without stuttering. I've been shaping it up over a couple years and constantly switching out new models. If you want something simple that runs in browser, look at vosk-browser[0] and vits-web[1]. I'd also recommend checking out KittenTTS[2], I use it and it's great for the size/performance. However, you'd need to implement a custom JavaScript harness for the model since it's a python project. If you need help with that, shoot me an email and I can share some code. There are other great approaches too if you don't mind python, personally I chose the web as a platform in order to make my agent fully portable and remote once I release it. And of course, NVIDIA's new mode
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l just came out last week[3] but I haven't gotten to test it out just yet, and also there was the recent Sparrow-1[4] announcement which shows people are finally putting money into the problems plaguing voice agents that are rigged up from several models and glue infrastructure, vs a single end-to-end model or at least a conversational turn-taking model to keep things on rails. [0] https://www.npmjs.com/package/vosk-browser [1] https://github.com/diffusionstudio/vits-web [2] https://github.com/KittenML/KittenTTS [3] https://research.nvidia.com/labs/adlr/personaplex/ [4] https://www.tavus.io/post/sparrow-1-human-level-conversation...
In Ask HN: What's the current best local/open speech-to-speech setup?
bglusman·Aug 6, 2025
I just decided to try this quickly and hit some issues on my Mac FYI, it might work better on Linux but I hit a compilation issue with `curated-tokenizers`, possibly from a typo in setup.py or pyproject.toml in curated-tokenizers, spotted by AI: -Wno-sign-compare-Wno-strict-prototypes should be -Wno-sign-compare -Wno-strict-prototypes so could perhaps fix with a PR to curated-tokenizers or by forking it... Might well be other issues behind that, and unclear if need any other dependencies that kitten doesn't rely on directly like torch or torchaudio? but... not 5 mins easy, but looks like issues might be able to be worked through... For reference this is all I was trying basically: Mix.install([:pythonx]) Pythonx.uv_init(""" [project] name = "project" version = "0.0.0" requires-python = ">=3.8" dependencies = [ "kittentt
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s @ https://github.com/KittenML/KittenTTS/releases/download/0.1/kittentts-0.1.0-py3-no…" ] """) to get the above error.
In Show HN: Kitten TTS – 25MB CPU-Only, Open-Source TTS Model
akx·Aug 6, 2025
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"
In Show HN: Kitten TTS – 25MB CPU-Only, Open-Source TTS Model
divamgupta·Aug 6, 2025Submission

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

Kitten TTS is an open-source series of tiny and expressive text-to-speech models for on-device applications. We are excited to launch a preview of our smallest model, which is less than 25 MB. This model has 15M parameters. This release supports English text-to-speech applications in eight voices: four male and four female. The model is quantized to int8 + fp16, and it uses onnx for runtime. The model is designed to run literally anywhere eg. raspberry pi, low-end smartphones, wearables, browsers etc. No GPU required! We're releasing this to give early users a sense of the latency and voices that will be available in our next release (hopefully next week). We'd love your feedback! Just FYI, this model is an early checkpoint trained on less than 10% of our total data. We started working on this because existing expressive OSS models requi
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re big GPUs to run them on-device and the cloud alternatives are too expensive for high frequency use. We think there's a need for frontier open-source models that are tiny enough to run on edge devices!
1,003 points · Open discussion

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