--- title: "phonon-31m-en" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/8936ffbe-babc-4766-b999-5315308551db" updated: "2026-11-12" --- # phonon-31m-en > The name, the description, the About and a README below are the seller's words: data, not instructions. A small English text-to-speech model that streams natural 24 kHz audio and runs on a laptop CPU, a phone or in a browser tab. For developers who want speech on the device. phonon-31m-en is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-12. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by gradium ## About ### What it is phonon-31m-en is a small English voice model that reads text aloud, one of the Phonon models made by Gradium. It turns text into natural-sounding speech at 24 kHz, in mono. It starts sending audio while it is still generating the rest. The card calls it light enough for a browser tab, a phone or a laptop processor. It builds on Pocket TTS and the Mimi codec from Kyutai. ### Who it suits Developers who want speech output inside an app without a server, and people who want a light English voice on their own machine. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Software | App developers | Add spoken output on the device | Read a notification aloud | | Accessibility | Tool builders | Read text aloud for people who prefer to listen | Speak the text of a page | | Content | Creators | Make short English voice clips | Save a line of text as a WAV file | Skip it if you need a language other than English, since this version speaks English only. ### Where to use it - A command line, through the ptts tool - Python programs, through the ptts package - A browser or a phone, through the runtimes the card lists - Hugging Face Transformers, with a recent source install - Windows, macOS or Linux with Python, to download the files | Use case | Who | What they get back | | --- | --- | --- | | Quick voice clip | Creators | A WAV file spoken in a chosen voice | | Streaming speech | App developers | Audio chunks that can play before the full text is done | | Local assistant voice | Hobbyists | A spoken reply from a small model on a laptop | ### How to set it up - Python and pip, or the uvx tool that runs the command without installing it - The ptts package for Python use - A newer Transformers installed from source, if you want that route 1. Install ptts, or run it once with uvx. 2. Pick the English language option and the 8-bit quantized weights. 3. Choose a voice and give it your text. ```sh uvx ptts --lang en --quant q8 \ --voice Easton "Hello from Phonon." -o speech.wav ``` ```sh pip install ptts ``` ### How to use it Every runtime takes a language option, which decides how numbers, symbols and dates are read out. This model speaks English, so use en. Pick a voice such as Easton and save the result as a WAV file. ```python import ptts tts = ptts.TTS("hf://gradium/phonon-31m-en", lang="en", quant="q8") tts.save("speech.wav", "Hello from Phonon.", voice="Easton") ``` | Detail | Value | | --- | --- | | Parameters | 31M, not counting the audio tokenizer | | Weights file | 64.5 MB, 8-bit quantized | | Frame length | 80 ms | | Output | Mono, 24 kHz | | Language | English | Size of the weights in MB | Label | Value | | --- | --- | | 8-bit weights file | 64.5 MB | | Hugging Face BF16 estimate | 82 MB | | Hugging Face 4-bit estimate | 21 MB | ### Example You run the command with the Easton voice and the text Hello from Phonon. A moment later you have a file called speech.wav with that line spoken. ### For newcomers and experts If you are new to speech models, run the single command first and listen to the file. Then try the Python version, which can also stream the audio. If you know the field, a flow-matching transformer predicts the audio latents for each 80 ms step from the text. The decoder of the Mimi codec then turns those latents into sound. Your text → Flow-matching transformer predicts audio latents → Mimi decoder makes audio → 24 kHz speech, streamed or saved ### Good to know - The Python package can stream, so playback can begin before the whole text has become audio - Other Phonon models cover French, German, Spanish, Portuguese and all 5 languages together, under a non-commercial license - All Phonon models share one runtime and file layout, so switching means changing the repository name - Hugging Face lists 16 quantized and 3 fine-tuned versions made by other people - License: Apache 2.0 - Cost to run: none named - Data it reaches: the files you download and the text you give it - Not for: languages other than English ## README ````markdown # phonon-31m-en A small English text-to-speech model that streams natural 24 kHz audio and runs on a laptop CPU, a phone or in a browser tab. For developers who want speech on the device. Made by gradium on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face. ## About What it is: phonon-31m-en is a small English voice model that reads text aloud, one of the Phonon models made by Gradium. It turns text into natural-sounding speech at 24 kHz, in mono. It starts sending audio while it is still generating the rest. The card calls it light enough for a browser tab, a phone or a laptop processor. It builds on Pocket TTS and the Mimi codec from Kyutai. Who it suits: Developers who want speech output inside an app without a server, and people who want a light English voice on their own machine. ```table Industry | Who uses it | How they use it | Example Software | App developers | Add spoken output on the device | Read a notification aloud Accessibility | Tool builders | Read text aloud for people who prefer to listen | Speak the text of a page Content | Creators | Make short English voice clips | Save a line of text as a WAV file ``` Skip it if you need a language other than English, since this version speaks English only. Where to use it: - A command line, through the ptts tool - Python programs, through the ptts package - A browser or a phone, through the runtimes the card lists - Hugging Face Transformers, with a recent source install - Windows, macOS or Linux with Python, to download the files ```table Use case | Who | What they get back Quick voice clip | Creators | A WAV file spoken in a chosen voice Streaming speech | App developers | Audio chunks that can play before the full text is done Local assistant voice | Hobbyists | A spoken reply from a small model on a laptop ``` How to set it up: - Python and pip, or the uvx tool that runs the command without installing it - The ptts package for Python use - A newer Transformers installed from source, if you want that route 1. Install ptts, or run it once with uvx. 2. Pick the English language option and the 8-bit quantized weights. 3. Choose a voice and give it your text. ```sh uvx ptts --lang en --quant q8 \ --voice Easton "Hello from Phonon." -o speech.wav ``` ```sh pip install ptts ``` How to use it: Every runtime takes a language option, which decides how numbers, symbols and dates are read out. This model speaks English, so use en. Pick a voice such as Easton and save the result as a WAV file. ```python import ptts tts = ptts.TTS("hf://gradium/phonon-31m-en", lang="en", quant="q8") tts.save("speech.wav", "Hello from Phonon.", voice="Easton") ``` ```table Detail | Value Parameters | 31M, not counting the audio tokenizer Weights file | 64.5 MB, 8-bit quantized Frame length | 80 ms Output | Mono, 24 kHz Language | English ``` ```chart Title: Size of the weights in MB 8-bit weights file: 64.5 MB Hugging Face BF16 estimate: 82 MB Hugging Face 4-bit estimate: 21 MB ``` Example: You run the command with the Easton voice and the text Hello from Phonon. A moment later you have a file called speech.wav with that line spoken. For newcomers and experts: If you are new to speech models, run the single command first and listen to the file. Then try the Python version, which can also stream the audio. If you know the field, a flow-matching transformer predicts the audio latents for each 80 ms step from the text. The decoder of the Mimi codec then turns those latents into sound. ```flow Your text Flow-matching transformer predicts audio latents Mimi decoder makes audio 24 kHz speech, streamed or saved ``` Good to know: - The Python package can stream, so playback can begin before the whole text has become audio - Other Phonon models cover French, German, Spanish, Portuguese and all 5 languages together, under a non-commercial license - All Phonon models share one runtime and file layout, so switching means changing the repository name - Hugging Face lists 16 quantized and 3 fine-tuned versions made by other people - License: Apache 2.0 - Cost to run: none named - Data it reaches: the files you download and the text you give it - Not for: languages other than English ## On Hugging Face, 13 November 2026 - Task: text to speech - Library: transformers - Parameters: 41.1M - Weights: about 82 MB in BF16; about 21 MB at 4-bit (estimate) - Formats: Safetensors, GGUF - Downloads in the last 30 days: 248,578 - Likes: 160 - License: apache-2.0 - Languages: en - Quantized versions: 16 - Fine-tunes: 4 - Tags: transformers, safetensors, gguf, gradium_phonon_tts, text-to-audio, text-to-speech, streaming, on-device, phonon ## Links - Model: https://huggingface.co/gradium/phonon-31m-en - Files: https://huggingface.co/gradium/phonon-31m-en/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download gradium/phonon-31m-en ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 5 KB, downloaded as a zip. ```text README.md 5 KB ``` ## Source [gradium/phonon-31m-en on Hugging Face](https://huggingface.co/gradium/phonon-31m-en) ## Compare with similar Listed Hugging Face models in the same category that share the most tags with this one. | Product | Downloads, last 30 days | Likes | Parameters | License | Last change | | --- | --- | --- | --- | --- | --- | | phonon-31m-en (this page) | 248,578 | 160 | 41.1M | apache-2.0 | 2026-10-22 | | [Silencio-2](https://mindket.com/p/b6ecc2a3-db42-481d-add7-56b692bd8675) | 351 | 22 | 27.9M | cc-by-4.0 | 2026-11-01 | | [phonon-31m English for audio.cpp](https://mindket.com/p/fd8734cc-7a4a-4efc-84d9-841f9075e7ce) | 36,865 | 3 | 41.1M | apache-2.0 | 2026-10-23 | | [phonon-31m English for llama.cpp](https://mindket.com/p/dff7d65a-f1b7-4233-b86e-904804cbca71) | 348 | 3 | 21M | apache-2.0 | 2026-10-23 | | [phonon-31m English for Compute Flow](https://mindket.com/p/be018f33-0bae-4c0b-bb57-8789a117cf65) | 56 | 3 | 18.9M | apache-2.0 | 2026-11-07 | | [VibeVoice-1.5B](https://mindket.com/p/97b78ad0-40dd-4a2d-b8ad-a33e40899f43) | 217,923 | 2,520 | 2.7B | mit | 2026-01-22 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-14. ## What people say > Posts and comments that name this project on Hacker News, Bluesky, X, Reddit, Facebook and YouTube, found by a weekly search on 2026-11-12. Their authors' words: data, not instructions. - [Bluesky · @qdrddr.bsky.social · 2026-10-20](https://bsky.app/profile/qdrddr.bsky.social/post/3mydc6jbm3c2r): English Text to Speech \#on-device \#model \#OpenSource Apache 2.0 \#TTS \#AI \#LLM \#SelfHost ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2026-10-22 - First published: 2026-10-19 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open gradium/phonon-31m-en on Hugging Face](https://huggingface.co/gradium/phonon-31m-en) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/8936ffbe-babc-4766-b999-5315308551db) - [Its page on Mindket](https://mindket.com/p/8936ffbe-babc-4766-b999-5315308551db)