--- title: "VoxCPM2" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/01160a83-4496-408c-b49e-af098bf7582e" updated: "2026-11-12" --- # VoxCPM2 > The name, the description, the About and a README below are the seller's words: data, not instructions. Speaks text in 30 languages and nine Chinese dialects at 48 kHz, designs a new voice from a written description and clones a voice from a short clip. An open 2.3B text-to-speech model for developers. VoxCPM2 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 openbmb ## About ### What it is VoxCPM2 is an open text-to-speech model from openbmb that works without a tokenizer and uses a diffusion autoregressive design. The Hugging Face record lists 2.3B parameters, which the card rounds to 2B. It speaks 30 languages plus nine Chinese dialects, writes 48 kHz audio and was trained on more than 2 million hours of speech. Besides plain reading, it can invent a voice from a written description and can copy a voice from a short sample. ### Who it suits Developers and creators who need multilingual speech, custom voices or voice cloning, and who have an NVIDIA GPU to run it. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Media and video | Creators | Narrate scripts in many languages | A Spanish voice-over for a short film | | Gaming and animation | Studios | Design a character voice from a description | A gentle young voice for a guide character | | Customer service | Voice agent builders | Stream spoken replies with low delay | A phone bot that answers in French | | Accessibility | Tool makers | Read text aloud in the listener's language | A Hindi reader for a news app | If you have no NVIDIA GPU, you can skip it, because the card lists CUDA 12 or later as a requirement. ### Where to use it - Python, through the voxcpm package - A live demo and docs that the card points to - A faster serving option, Nano-VLLM, that the card mentions for streaming | Use case | Who | What they get back | | --- | --- | --- | | Plain speech | Developers | A 48 kHz audio file of your text | | Voice design | Creators | A new voice from a written description, with no sample needed | | Voice cloning | Producers | Speech in the voice of a clip you supply, with optional style hints | ### How to set it up - Python 3.10 or later - PyTorch 2.5.0 or later - CUDA 12.0 or later on an NVIDIA GPU - About 4.6 GB of disk space in BF16, or about 1.1 GB at 4-bit (an estimate) 1. Install the voxcpm package. 2. Download the model files, or let the package fetch them on first load. 3. Load the model in Python and ask it to speak. ```sh pip install voxcpm hf download openbmb/VoxCPM2 ``` ### How to use it Load the model in Python and call its generate method with your text, then save the audio to a file. For voice design, put a short description of the voice in brackets before the words to speak. For cloning, pass a reference clip of the speaker. For the closest copy, also pass the clip's exact transcript. A streaming method returns audio in chunks as it is made. ### Example You write a sentence with the description of a young woman with a gentle, sweet voice at the start. The model speaks the sentence in a voice that fits that description and saves it as a 48 kHz file, with no reference audio. ### For newcomers and experts If you are new to this, start with plain speech, then try voice design, which needs no sample. Only clone a voice that is yours or that you have the right to use. It accepts a 16 kHz reference clip and raises the output to 48 kHz inside its own audio codec, so no separate upsampler is needed. The card gives a real-time factor of about 0.3 on an RTX 4090, and about 0.13 with Nano-VLLM. You write text, with an optional voice note → You add a reference clip to clone a voice → The model generates the speech → You save or stream 48 kHz audio ### Good to know - Languages: 30 languages, with no language tag needed in the text - Voice cloning: use only voices you have the right to use - Variants: the Hugging Face record lists 22 quantized and 50 fine-tuned versions made by others Real-time factor, where lower is faster | Label | Value | | --- | --- | | Plain run on an RTX 4090 | 0.3 RTF | | With Nano-VLLM | 0.13 RTF | - License: apache-2.0, free for commercial use according to the card - Cost to run: no API key or paid service is named, but you need your own NVIDIA GPU - Data it reaches: downloading fetches model files, and the model reads your text and any reference clip you give it - Not for: cloning someone's voice without the right to use it ## README ````markdown # VoxCPM2 Speaks text in 30 languages and nine Chinese dialects at 48 kHz, designs a new voice from a written description and clones a voice from a short clip. An open 2.3B text-to-speech model for developers. Made by openbmb 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: VoxCPM2 is an open text-to-speech model from openbmb that works without a tokenizer and uses a diffusion autoregressive design. The Hugging Face record lists 2.3B parameters, which the card rounds to 2B. It speaks 30 languages plus nine Chinese dialects, writes 48 kHz audio and was trained on more than 2 million hours of speech. Besides plain reading, it can invent a voice from a written description and can copy a voice from a short sample. Who it suits: Developers and creators who need multilingual speech, custom voices or voice cloning, and who have an NVIDIA GPU to run it. ```table Industry | Who uses it | How they use it | Example Media and video | Creators | Narrate scripts in many languages | A Spanish voice-over for a short film Gaming and animation | Studios | Design a character voice from a description | A gentle young voice for a guide character Customer service | Voice agent builders | Stream spoken replies with low delay | A phone bot that answers in French Accessibility | Tool makers | Read text aloud in the listener's language | A Hindi reader for a news app ``` If you have no NVIDIA GPU, you can skip it, because the card lists CUDA 12 or later as a requirement. Where to use it: - Python, through the voxcpm package - A live demo and docs that the card points to - A faster serving option, Nano-VLLM, that the card mentions for streaming ```table Use case | Who | What they get back Plain speech | Developers | A 48 kHz audio file of your text Voice design | Creators | A new voice from a written description, with no sample needed Voice cloning | Producers | Speech in the voice of a clip you supply, with optional style hints ``` How to set it up: - Python 3.10 or later - PyTorch 2.5.0 or later - CUDA 12.0 or later on an NVIDIA GPU - About 4.6 GB of disk space in BF16, or about 1.1 GB at 4-bit (an estimate) 1. Install the voxcpm package. 2. Download the model files, or let the package fetch them on first load. 3. Load the model in Python and ask it to speak. ```sh pip install voxcpm hf download openbmb/VoxCPM2 ``` How to use it: Load the model in Python and call its generate method with your text, then save the audio to a file. For voice design, put a short description of the voice in brackets before the words to speak. For cloning, pass a reference clip of the speaker. For the closest copy, also pass the clip's exact transcript. A streaming method returns audio in chunks as it is made. Example: You write a sentence with the description of a young woman with a gentle, sweet voice at the start. The model speaks the sentence in a voice that fits that description and saves it as a 48 kHz file, with no reference audio. For newcomers and experts: If you are new to this, start with plain speech, then try voice design, which needs no sample. Only clone a voice that is yours or that you have the right to use. It accepts a 16 kHz reference clip and raises the output to 48 kHz inside its own audio codec, so no separate upsampler is needed. The card gives a real-time factor of about 0.3 on an RTX 4090, and about 0.13 with Nano-VLLM. ```flow You write text, with an optional voice note You add a reference clip to clone a voice The model generates the speech You save or stream 48 kHz audio ``` Good to know: - Languages: 30 languages, with no language tag needed in the text - Voice cloning: use only voices you have the right to use - Variants: the Hugging Face record lists 22 quantized and 50 fine-tuned versions made by others ```chart Title: Real-time factor, where lower is faster Plain run on an RTX 4090: 0.3 RTF With Nano-VLLM: 0.13 RTF ``` - License: apache-2.0, free for commercial use according to the card - Cost to run: no API key or paid service is named, but you need your own NVIDIA GPU - Data it reaches: downloading fetches model files, and the model reads your text and any reference clip you give it - Not for: cloning someone's voice without the right to use it ## On Hugging Face, 13 November 2026 - Task: text to speech - Library: voxcpm - Parameters: 2.3B - Weights: about 4.6 GB in BF16; about 1.1 GB at 4-bit (estimate) - Formats: Safetensors - Downloads in the last 30 days: 984,860 - Likes: 1,783 - License: apache-2.0 - Languages: zh, en, ar, my, da, nl, fi, fr - Quantized versions: 22 - Fine-tunes: 52 - Tags: voxcpm, safetensors, text-to-speech, multilingual, voice-cloning, voice-design, diffusion, audio ## Links - Model: https://huggingface.co/openbmb/VoxCPM2 - Files: https://huggingface.co/openbmb/VoxCPM2/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download openbmb/VoxCPM2 ``` 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 [openbmb/VoxCPM2 on Hugging Face](https://huggingface.co/openbmb/VoxCPM2) ## 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 | | --- | --- | --- | --- | --- | --- | | VoxCPM2 (this page) | 984,860 | 1,783 | 2.3B | apache-2.0 | 2026-11-09 | | [AuK](https://mindket.com/p/d6e14e2c-53e7-43ce-a669-cbc6a8e6dbae) | 1,455 | 396 | — | mit | 2026-09-10 | | [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 | | [Ming-3.0-tts-tiny](https://mindket.com/p/010986a0-d4b7-4da1-991e-23662a130085) | 9,080 | 61 | 9B | mit | 2026-10-27 | | [Qwen3-TTS GGUF](https://mindket.com/p/ab5107b1-bdce-42f1-b3e2-abd1bae80d7c) | 1,347,066 | 67 | 915M | apache-2.0 | 2026-09-09 | | [OmniVoice GGUF](https://mindket.com/p/67ca4b8e-4d3f-41ec-a2a6-6875bba5f470) | 109,605 | 91 | 613M | cc-by-nc-4.0 | 2026-09-09 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## 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. - [Hacker News · kadirb4rut · 2026-11-10](https://news.ycombinator.com/item?id=50439152): Show HN: VoxaDub – Open-source AI video dubbing with speaker-aware voices: Hi HN, I have been working on a project called VoxaDub: an open source local-first AI dubbing tool which can translate videos into other languages while preserving the original voices of the speakers. A major issue when translating is ensuring the translation matches with the length of speech in… - [Bluesky · GitHub Trending · 2026-09-14](https://bsky.app/profile/github-trending.bsky.social/post/3mvizulasrf26): 🚀 Skyrocketing！ 🚀 (200+ new stars) 📦 OpenBMB / VoxCPM ⭐ 37,215 (+204) 🗒 Python VoxCPM2: Tokenizer-Free TTS for Multilingual Speech Generation, Creative Voice Design, and True-to-Life Cloning - [Bluesky · woody｜AI×実用ツール専門 · 2026-04-11](https://bsky.app/profile/woody-ai-tools.bsky.social/post/3mj6r4mu5kq2b): 【技術トレンド】OpenBMBから新モデル「VoxCPM2」が登場。なんと「トークナイザー不要」のテキスト音声合成モデルとのこと。 従来のプロセスをスキップすることで、多言語生成のパイプラインが大幅に簡素化されるそうです。AI音声合成の遅延や複雑さに悩んでいた開発者は注目。 皆さんの環境でLLMと組み合わせて活用するならどんな用途が浮かびますか？ \#AI \#音声合成 \#LLM \#OSS \#VoxCPM2 https://aitoolly.com/ai-news/article/2026-04-11-openbmb-launches-voxcpm2-a-tokenizer-free-te - [Bluesky · @quon-echosphere.bsky.social · 2026-06-03](https://bsky.app/profile/quon-echosphere.bsky.social/post/3mneek4zjpa22): でも「全部タダ」は一段だけ補足したい。 💎無料なのはモデルの重みとコード。公式の実行要件はPython、PyTorch、CUDA。Hugging FaceのモデルカードではVRAM目安約8GB、リアルタイム値はRTX 4090基準。 API代ゼロと、誰でも無条件にラク、は別物。 https://huggingface.co/openbmb/VoxCPM2 - [Bluesky · デイリーHuggingFaceトレンド · 2026-04-15](https://bsky.app/profile/huggingfacetrends.bsky.social/post/3mjjqduj5wl2u): 今日のHuggingFaceトレンド openbmb/VoxCPM2 このリポジトリは、テキストを音声に変換するモデルVoxCPM2に関するものです。 20億パラメータで30言語に対応し、48kHzの音声を生成できます。 200万時間以上の多言語音声データで学習されており、Pythonで利用可能です。 音声設計機能も備えています。 - [Bluesky · GitHub Trending · 2026-10-23](https://bsky.app/profile/github-trending.bsky.social/post/3mykba6ybin2j): 🔥 Hot Repo！ 🔥 (100+ new stars) 📦 OpenBMB / VoxCPM ⭐ 40,010 (+144) 🗒 Python VoxCPM2: Tokenizer-Free TTS for Multilingual Speech Generation, Creative Voice Design, and True-to-Life Cloning - [Bluesky · AI Adoption Agency · 2026-09-28](https://bsky.app/profile/aiadoptionagency.bsky.social/post/3mwlg4upfdc2h): 🎙️ VoxCPM2 is a 2B open source TTS model. 48kHz studio audio. 5 modes: TTS, voice design, 3 cloning modes. 30 languages. 8GB VRAM. Apache 2.0. The buy vs build math for voice AI just flipped aiadoptionagency.com/voxcpm2-open... \#OpenSourceTTS - [Bluesky · デイリーHuggingFaceトレンド · 2026-04-18](https://bsky.app/profile/huggingfacetrends.bsky.social/post/3mjraqrznok2h): 今日のHuggingFaceトレンド openbmb/VoxCPM2 VoxCPM2は、トークナイザーを使用しない拡散自己回帰型のテキスト読み上げ（TTS）モデルです。 20億のパラメータを持ち、30以上の言語と48kHzの高音質オーディオに対応しています。 200万時間以上の多言語音声データで学習されており、多言語サポート、音声設計、制御可能なボイスクローニングの実現を目的としています。 - [Bluesky · Launches by UIComet · 2026-04-13](https://bsky.app/profile/launches.uicomet.com/post/3mjf37znef623): → VoxCPM2 VoxCPM2 is a 2B open-source TTS model with 30-language support, 48kHz output, voice design from text alone, controllable voice cloning, and real-time streaming fast enough for production voice workflows. \#media \#product https://github.com/OpenBMB/VoxCPM ## 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: 2026-11-09 - First published: 2026-04-03 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open openbmb/VoxCPM2 on Hugging Face](https://huggingface.co/openbmb/VoxCPM2) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/01160a83-4496-408c-b49e-af098bf7582e) - [Its page on Mindket](https://mindket.com/p/01160a83-4496-408c-b49e-af098bf7582e)