--- title: "phonon-31m English for llama.cpp" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/dff7d65a-f1b7-4233-b86e-904804cbca71" updated: "2026-11-13" --- # phonon-31m English for llama.cpp > The name, the description, the About and a README below are the seller's words: data, not instructions. Turns English text into speech from the command line or a local server, as a GGUF copy of the Phonon 31M model for llama.cpp. It suits developers who already run llama.cpp with a Phonon-enabled build. phonon-31m English for llama.cpp is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-13. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by gradium ## About ### What it is This is the GGUF conversion of the Phonon 31M English model, made for the llama-tts and llama-server programs of llama.cpp. It reads English text and writes speech. The model is the same, and only the file format differs. It works only with a llama.cpp build that has Phonon support, and that support has not been merged into the main project yet. ### Who it suits Developers who already run llama.cpp and want local English speech from text suit it best. No cloud service is involved. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Software | Developers | Add local text to speech to an app through the llama.cpp server | Send text to the server and save the audio | | Voice tools | Hobbyists | Make speech files from the command line | Turn one sentence into a wav file | | Research | Audio researchers | Test a small speech model inside the llama.cpp ecosystem | Compare it with the Phonon runtime | Anyone who wants voice cloning, another language, or Phonon on a phone or in a browser can skip it and use the main Phonon model. ### Where to use it It runs through two llama.cpp programs, on any computer where you have a Phonon-ready llama.cpp build. - llama-tts, for speech files from the command line - llama-server, for a local server that returns audio - A llama.cpp build with Phonon support - Windows, macOS or Linux with Python for the file download | Use case | Who | What they get back | | --- | --- | --- | | Speech files | Developers | A wav file for a line of English text | | Local speech server | Developers | Audio returned for each text request | | Offline voice features | Hobbyists | Speech made on your own machine | ### How to set it up You need a build of llama.cpp that includes Phonon, plus the two model files. The record estimates about 11 MB at 4-bit, so disk space is small. - A llama.cpp build that has Phonon support - Python and the huggingface\_hub package, if you download the files yourself - Both model files, because llama.cpp needs the two together | File | What it holds | | --- | --- | | Model file | The main speech transformer in 8-bit, plus the tokenizer and a built-in voice | | Projector file | The Mimi decoder and the flow head, kept at full precision | 1. Get a llama.cpp build with Phonon support. 2. Install the hub tools with pip. 3. Download the model files with the hf command. 4. Run llama-tts or llama-server with the two files. ```sh pip install -U huggingface_hub hf download gradium/phonon-31m-en-llamacpp ``` ### How to use it The model file goes in with the -m flag, and the projector file goes in with -mm. The first command below lets llama-tts fetch the files and speak one line. ```sh llama-tts -hf gradium/phonon-31m-en-llamacpp -p "Hello from Phonon." -o speech.wav ``` With the files already downloaded, you name both of them yourself. ```sh llama-tts -m phonon-31m-en-Q8_0.gguf -mm mmproj-phonon-31m-en-F32.gguf \ -p "Hello from Phonon." -o speech.wav ``` To run it as a server, start llama-server on a port. Then send a POST request to its tts path with a JSON body that holds your input text, and save the reply as a wav file. ```sh llama-server -hf gradium/phonon-31m-en-llamacpp --port 8080 ``` ### Example You run the first command with a short English sentence in the -p flag. It writes a wav file with that sentence spoken aloud. ### For newcomers and experts Think of this as a tiny voice that reads English text aloud on your own computer. Your first small try is to run the first command with a short sentence, once you have a Phonon-ready llama.cpp build. Under the hood, the main file holds a flow-matching transformer in 8-bit, and the projector file holds the flow head and the Mimi decoder. Phonon builds on Pocket TTS and the Mimi codec from Kyutai. The trade-off is limited voices and a build that is not yet in the main project. Your English text → llama.cpp tokenizer → Phonon transformer and flow head → Mimi decoder makes the audio → Speech saved as a wav file ### Good to know Several limits come from how llama.cpp handles text and voices today. - Voice: a default voice is built in, so you need no speaker file, and there is no voice cloning from audio - Other voices: the extra voices in the Phonon voices collection do not work in llama.cpp yet - Text: llama.cpp passes your text to the tokenizer as written, so spell out numbers, symbols and short forms as words - Phonon runtime: it spells these out for you when you use --lang en - Characters: emoji and letters the tokenizer lacks reach the model as an unknown token, so use plain text - Sampling: temperature 0.3, the same default as the Phonon runtime - Size: 21M parameters in the record, in GGUF format, English only - License: apache-2.0 - Cost to run: none named - Data it reaches: the text you give it, and the files downloaded from Hugging Face ## README ````markdown # phonon-31m English for llama.cpp Turns English text into speech from the command line or a local server, as a GGUF copy of the Phonon 31M model for llama.cpp. It suits developers who already run llama.cpp with a Phonon-enabled build. 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: This is the GGUF conversion of the Phonon 31M English model, made for the llama-tts and llama-server programs of llama.cpp. It reads English text and writes speech. The model is the same, and only the file format differs. It works only with a llama.cpp build that has Phonon support, and that support has not been merged into the main project yet. Who it suits: Developers who already run llama.cpp and want local English speech from text suit it best. No cloud service is involved. ```table Industry | Who uses it | How they use it | Example Software | Developers | Add local text to speech to an app through the llama.cpp server | Send text to the server and save the audio Voice tools | Hobbyists | Make speech files from the command line | Turn one sentence into a wav file Research | Audio researchers | Test a small speech model inside the llama.cpp ecosystem | Compare it with the Phonon runtime ``` Anyone who wants voice cloning, another language, or Phonon on a phone or in a browser can skip it and use the main Phonon model. Where to use it: It runs through two llama.cpp programs, on any computer where you have a Phonon-ready llama.cpp build. - llama-tts, for speech files from the command line - llama-server, for a local server that returns audio - A llama.cpp build with Phonon support - Windows, macOS or Linux with Python for the file download ```table Use case | Who | What they get back Speech files | Developers | A wav file for a line of English text Local speech server | Developers | Audio returned for each text request Offline voice features | Hobbyists | Speech made on your own machine ``` How to set it up: You need a build of llama.cpp that includes Phonon, plus the two model files. The record estimates about 11 MB at 4-bit, so disk space is small. - A llama.cpp build that has Phonon support - Python and the huggingface_hub package, if you download the files yourself - Both model files, because llama.cpp needs the two together ```table File | What it holds Model file | The main speech transformer in 8-bit, plus the tokenizer and a built-in voice Projector file | The Mimi decoder and the flow head, kept at full precision ``` 1. Get a llama.cpp build with Phonon support. 2. Install the hub tools with pip. 3. Download the model files with the hf command. 4. Run llama-tts or llama-server with the two files. ```sh pip install -U huggingface_hub hf download gradium/phonon-31m-en-llamacpp ``` How to use it: The model file goes in with the -m flag, and the projector file goes in with -mm. The first command below lets llama-tts fetch the files and speak one line. ```sh llama-tts -hf gradium/phonon-31m-en-llamacpp -p "Hello from Phonon." -o speech.wav ``` With the files already downloaded, you name both of them yourself. ```sh llama-tts -m phonon-31m-en-Q8_0.gguf -mm mmproj-phonon-31m-en-F32.gguf \ -p "Hello from Phonon." -o speech.wav ``` To run it as a server, start llama-server on a port. Then send a POST request to its tts path with a JSON body that holds your input text, and save the reply as a wav file. ```sh llama-server -hf gradium/phonon-31m-en-llamacpp --port 8080 ``` Example: You run the first command with a short English sentence in the -p flag. It writes a wav file with that sentence spoken aloud. For newcomers and experts: Think of this as a tiny voice that reads English text aloud on your own computer. Your first small try is to run the first command with a short sentence, once you have a Phonon-ready llama.cpp build. Under the hood, the main file holds a flow-matching transformer in 8-bit, and the projector file holds the flow head and the Mimi decoder. Phonon builds on Pocket TTS and the Mimi codec from Kyutai. The trade-off is limited voices and a build that is not yet in the main project. ```flow Your English text llama.cpp tokenizer Phonon transformer and flow head Mimi decoder makes the audio Speech saved as a wav file ``` Good to know: Several limits come from how llama.cpp handles text and voices today. - Voice: a default voice is built in, so you need no speaker file, and there is no voice cloning from audio - Other voices: the extra voices in the Phonon voices collection do not work in llama.cpp yet - Text: llama.cpp passes your text to the tokenizer as written, so spell out numbers, symbols and short forms as words - Phonon runtime: it spells these out for you when you use --lang en - Characters: emoji and letters the tokenizer lacks reach the model as an unknown token, so use plain text - Sampling: temperature 0.3, the same default as the Phonon runtime - Size: 21M parameters in the record, in GGUF format, English only - License: apache-2.0 - Cost to run: none named - Data it reaches: the text you give it, and the files downloaded from Hugging Face ## On Hugging Face, 13 November 2026 - Task: text to speech - Library: gguf - Parameters: 21M - Weights: about 11 MB at 4-bit (estimate) - Formats: GGUF - Downloads in the last 30 days: 348 - Likes: 3 - License: apache-2.0 - Languages: en - Based on: gradium/phonon-31m-en - Tags: gguf, text-to-speech, phonon, llama.cpp ## Links - Model: https://huggingface.co/gradium/phonon-31m-en-llamacpp - Files: https://huggingface.co/gradium/phonon-31m-en-llamacpp/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-llamacpp ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 6 KB, downloaded as a zip. ```text README.md 6 KB ``` ## Source [gradium/phonon-31m-en-llamacpp on Hugging Face](https://huggingface.co/gradium/phonon-31m-en-llamacpp) ## 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 English for llama.cpp (this page) | 348 | 3 | 21M | apache-2.0 | 2026-10-23 | | [phonon-31m-en](https://mindket.com/p/8936ffbe-babc-4766-b999-5315308551db) | 248,578 | 160 | 41.1M | apache-2.0 | 2026-10-22 | | [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 Compute Flow](https://mindket.com/p/be018f33-0bae-4c0b-bb57-8789a117cf65) | 56 | 3 | 18.9M | apache-2.0 | 2026-11-07 | | [ZONOS3-Mini GGUF](https://mindket.com/p/36a9f74c-420d-4d5c-88a8-0864cda4d231) | 385 | 9 | 802M | apache-2.0 | 2026-11-10 | | [VieNeu-TTS v3 Turbo](https://mindket.com/p/1dc8a3b8-2ee4-414e-bca9-d273eb678fee) | 2,151,800 | 109 | 131M | apache-2.0 | 2026-09-23 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## 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: 2026-10-23 - First published: 2026-10-23 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open gradium/phonon-31m-en-llamacpp on Hugging Face](https://huggingface.co/gradium/phonon-31m-en-llamacpp) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/dff7d65a-f1b7-4233-b86e-904804cbca71) - [Its page on Mindket](https://mindket.com/p/dff7d65a-f1b7-4233-b86e-904804cbca71)