--- title: "Spark-TTS-0.5B" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/a2b3e587-e561-4ce8-91ca-86355c6efa9d" updated: "2026-11-13" --- # Spark-TTS-0.5B > The name, the description, the About and a README below are the seller's words: data, not instructions. Speaks Chinese and English from text with a Qwen2.5-based model, including zero-shot voice cloning and virtual voices set by gender, pitch and speaking rate. For developers and researchers working on speech. Spark-TTS-0.5B 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 SparkAudio ## About ### What it is Spark-TTS-0.5B is a text-to-speech model built on Qwen2.5. It needs no separate generation model such as flow matching, because it rebuilds audio directly from the codes the language model predicts. It speaks Chinese and English, clones a voice without training on it, and can create virtual speakers by adjusting gender, pitch and speaking rate. ### Who it suits It suits developers and researchers who want a speech model for Chinese and English that runs on their own machine. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Software | Voice app developers | Add Chinese and English speech to an application | Reading app text aloud from a script | | Media | Narration makers | Create a virtual speaker by setting gender, pitch and rate | Voicing a personal, non-commercial video | | Localization | Bilingual teams | Switch between Chinese and English in cloned speech | Speaking a sentence that mixes both languages | | Research | Speech researchers | Study speech generation driven by a language model | Running the demo script and listening to the output | If you need commercial use, or want to clone a voice you have no right to use, you can skip it. Use only voices you have permission for. ### Where to use it - A terminal with a Conda environment on Python 3.12 - The web interface started by webui.py, with Voice Cloning and Voice Creation - Windows, macOS or Linux with Python, for downloading the files | Use case | Who | What they get back | | --- | --- | --- | | Voice cloning | Researchers | Speech in the voice of a short reference recording | | Voice creation | Content makers | Speech from a virtual speaker with the gender, pitch and rate you set | | Demo run | Newcomers | An audio file from the example script | ### How to set it up - Git and Conda - Python 3.12 inside a Conda environment - The Spark-TTS code from its GitHub page - The model files, downloaded with Python or with Git LFS 1. Clone the Spark-TTS repository from GitHub and move into it. The card gives the clone command, which holds a web address, so copy it from there. 2. Create and activate the Conda environment. 3. Install the requirements. The card also lists a mirror option for users in mainland China. 4. Download the model into the pretrained\_models folder. ```sh conda create -n sparktts -y python=3.12 conda activate sparktts pip install -r requirements.txt ``` ```python from huggingface_hub import snapshot_download snapshot_download("SparkAudio/Spark-TTS-0.5B", local_dir="pretrained_models/Spark-TTS-0.5B") ``` ### How to use it Run the demo from the example folder, or call the command line interface yourself. You can also start the web interface, which lets you clone a voice from uploaded or recorded audio, or create a voice. ```sh cd example bash infer.sh ``` ```sh python -m cli.inference \ --text "text to synthesis." \ --device 0 \ --save_dir "path/to/save/audio" \ --model_dir pretrained_models/Spark-TTS-0.5B \ --prompt_text "transcript of the prompt audio" \ --prompt_speech_path "path/to/prompt_audio" ``` ```sh python webui.py ``` | Tool | What it does | | --- | --- | | infer.sh | Runs the demo from the example folder | | cli.inference | Synthesizes speech from text, with an optional prompt recording and its transcript | | webui.py | Starts the web interface for Voice Cloning and Voice Creation | | --save\_dir | Sets the folder where the audio is saved | ### Example You run the command line tool with the text to speak, a short prompt recording and a transcript of that recording. The model saves speech in the voice of the prompt into the folder you named. Clone only voices you have the right to use. ### For newcomers and experts A language model normally predicts words. Here it predicts codes that stand for sounds, and a decoder turns those codes into audio. A good first try is the demo script in the example folder. Under the hood, the paper title in the card describes single-stream decoupled speech tokens. The language model predicts those tokens and the audio is rebuilt from them directly. The Qwen2.5 base keeps the system simple. The hub lists 6 quantized and 25 fine-tuned versions made by other people. Text, and optional prompt audio → Language model predicts speech codes → Codes are rebuilt directly into audio → Audio file is saved ### Good to know - The training code and the VoxBox training dataset are not released yet, according to the card's to-do list. - License: CC BY-NC-SA 4.0, which does not allow commercial use - Cost to run: none named - Data it reaches: the text and prompt audio you give it, and the model files downloaded from the Hugging Face hub - Not for: commercial use, and cloning voices without the right to use them ## README ````markdown # Spark-TTS-0.5B Speaks Chinese and English from text with a Qwen2.5-based model, including zero-shot voice cloning and virtual voices set by gender, pitch and speaking rate. For developers and researchers working on speech. Made by SparkAudio 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: Spark-TTS-0.5B is a text-to-speech model built on Qwen2.5. It needs no separate generation model such as flow matching, because it rebuilds audio directly from the codes the language model predicts. It speaks Chinese and English, clones a voice without training on it, and can create virtual speakers by adjusting gender, pitch and speaking rate. Who it suits: It suits developers and researchers who want a speech model for Chinese and English that runs on their own machine. ```table Industry | Who uses it | How they use it | Example Software | Voice app developers | Add Chinese and English speech to an application | Reading app text aloud from a script Media | Narration makers | Create a virtual speaker by setting gender, pitch and rate | Voicing a personal, non-commercial video Localization | Bilingual teams | Switch between Chinese and English in cloned speech | Speaking a sentence that mixes both languages Research | Speech researchers | Study speech generation driven by a language model | Running the demo script and listening to the output ``` If you need commercial use, or want to clone a voice you have no right to use, you can skip it. Use only voices you have permission for. Where to use it: - A terminal with a Conda environment on Python 3.12 - The web interface started by webui.py, with Voice Cloning and Voice Creation - Windows, macOS or Linux with Python, for downloading the files ```table Use case | Who | What they get back Voice cloning | Researchers | Speech in the voice of a short reference recording Voice creation | Content makers | Speech from a virtual speaker with the gender, pitch and rate you set Demo run | Newcomers | An audio file from the example script ``` How to set it up: - Git and Conda - Python 3.12 inside a Conda environment - The Spark-TTS code from its GitHub page - The model files, downloaded with Python or with Git LFS 1. Clone the Spark-TTS repository from GitHub and move into it. The card gives the clone command, which holds a web address, so copy it from there. 2. Create and activate the Conda environment. 3. Install the requirements. The card also lists a mirror option for users in mainland China. 4. Download the model into the pretrained_models folder. ```sh conda create -n sparktts -y python=3.12 conda activate sparktts pip install -r requirements.txt ``` ```python from huggingface_hub import snapshot_download snapshot_download("SparkAudio/Spark-TTS-0.5B", local_dir="pretrained_models/Spark-TTS-0.5B") ``` How to use it: Run the demo from the example folder, or call the command line interface yourself. You can also start the web interface, which lets you clone a voice from uploaded or recorded audio, or create a voice. ```sh cd example bash infer.sh ``` ```sh python -m cli.inference \ --text "text to synthesis." \ --device 0 \ --save_dir "path/to/save/audio" \ --model_dir pretrained_models/Spark-TTS-0.5B \ --prompt_text "transcript of the prompt audio" \ --prompt_speech_path "path/to/prompt_audio" ``` ```sh python webui.py ``` ```table Tool | What it does infer.sh | Runs the demo from the example folder cli.inference | Synthesizes speech from text, with an optional prompt recording and its transcript webui.py | Starts the web interface for Voice Cloning and Voice Creation --save_dir | Sets the folder where the audio is saved ``` Example: You run the command line tool with the text to speak, a short prompt recording and a transcript of that recording. The model saves speech in the voice of the prompt into the folder you named. Clone only voices you have the right to use. For newcomers and experts: A language model normally predicts words. Here it predicts codes that stand for sounds, and a decoder turns those codes into audio. A good first try is the demo script in the example folder. Under the hood, the paper title in the card describes single-stream decoupled speech tokens. The language model predicts those tokens and the audio is rebuilt from them directly. The Qwen2.5 base keeps the system simple. The hub lists 6 quantized and 25 fine-tuned versions made by other people. ```flow Text, and optional prompt audio Language model predicts speech codes Codes are rebuilt directly into audio Audio file is saved ``` Good to know: - The training code and the VoxBox training dataset are not released yet, according to the card's to-do list. - License: CC BY-NC-SA 4.0, which does not allow commercial use - Cost to run: none named - Data it reaches: the text and prompt audio you give it, and the model files downloaded from the Hugging Face hub - Not for: commercial use, and cloning voices without the right to use them ## On Hugging Face, 13 November 2026 - Task: text to speech - Formats: Safetensors - Downloads in the last 30 days: 2,124 - Likes: 750 - License: cc-by-nc-sa-4.0 - Languages: en, zh - Quantized versions: 6 - Fine-tunes: 25 - Tags: safetensors, text-to-speech ## Links - Model: https://huggingface.co/SparkAudio/Spark-TTS-0.5B - Files: https://huggingface.co/SparkAudio/Spark-TTS-0.5B/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download SparkAudio/Spark-TTS-0.5B ``` 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 [SparkAudio/Spark-TTS-0.5B on Hugging Face](https://huggingface.co/SparkAudio/Spark-TTS-0.5B) ## 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 | | --- | --- | --- | --- | --- | --- | | Spark-TTS-0.5B (this page) | 2,124 | 750 | — | cc-by-nc-sa-4.0 | 2025-03-07 | | [VieNeu-TTS v3 Turbo](https://mindket.com/p/1dc8a3b8-2ee4-414e-bca9-d273eb678fee) | 2,151,800 | 109 | 131M | apache-2.0 | 2026-09-23 | | [VoxCPM2](https://mindket.com/p/01160a83-4496-408c-b49e-af098bf7582e) | 984,860 | 1,783 | 2.3B | apache-2.0 | 2026-11-09 | | [phonon-31m-en](https://mindket.com/p/8936ffbe-babc-4766-b999-5315308551db) | 248,578 | 160 | 41.1M | apache-2.0 | 2026-10-22 | | [MOSS-TTS-v1.5](https://mindket.com/p/3d56747c-ea45-4083-be08-1071cec8fc5b) | 80,361 | 220 | 8.5B | apache-2.0 | 2026-05-26 | | [Ming-3.0-tts-0.5B by inclusionAI](https://mindket.com/p/f13d7a41-4e55-40ee-b52d-b5fd3d09578b) | 14,756 | 225 | 1.5B | mit | 2026-10-27 | 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: 2025-03-07 - First published: 2025-02-27 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open SparkAudio/Spark-TTS-0.5B on Hugging Face](https://huggingface.co/SparkAudio/Spark-TTS-0.5B) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/a2b3e587-e561-4ce8-91ca-86355c6efa9d) - [Its page on Mindket](https://mindket.com/p/a2b3e587-e561-4ce8-91ca-86355c6efa9d)