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voxcpm

2B-parameter text-to-speech model with voice design and voice cloning

Stars
39.3k
License
Apache-2.0
Last commit
Oct 2026
Last release
May 2026
Language
Python
Stars, last 29 weeks+33,253
25 Mar 2026: 6,057 stars1 Apr 2026: 6,101 stars8 Apr 2026: 7,046 stars15 Apr 2026: 13,102 stars22 Apr 2026: 15,206 stars29 Apr 2026: 15,835 stars6 May 2026: 17,096 stars13 May 2026: 18,312 stars20 May 2026: 18,871 stars27 May 2026: 19,573 stars3 Jun 2026: 25,184 stars10 Jun 2026: 27,847 stars17 Jun 2026: 30,067 stars24 Jun 2026: 31,165 stars1 Jul 2026: 31,880 stars8 Jul 2026: 32,450 stars15 Jul 2026: 33,038 stars22 Jul 2026: 33,702 stars29 Jul 2026: 34,211 stars5 Aug 2026: 34,666 stars12 Aug 2026: 35,126 stars19 Aug 2026: 35,622 stars26 Aug 2026: 35,914 stars2 Sept 2026: 36,373 stars9 Sept 2026: 36,710 stars16 Sept 2026: 37,468 stars23 Sept 2026: 37,756 stars30 Sept 2026: 38,098 stars7 Oct 2026: 38,294 stars14 Oct 2026: 39,310 stars

6,057 on 25 Mar 202639,310 on 14 Oct 2026

From GitHub's daily star counts.

Checked on GitHub.

Overview

VoxCPM2 is a 2B-parameter, tokenizer-free TTS model built on a MiniCPM-4 backbone. It synthesizes 48kHz speech in 30 languages, creates voices from a text description, and clones voices from a short reference clip, optionally with a transcript for continuation cloning. It ships as a pip package with a Python API, CLI and web demo, and can be served through Nano-vLLM, vLLM-Omni or llama.cpp-omni.

Who it is for: Developers needing self-hosted multilingual TTS, voice design or voice cloning

Strengths

  • Voice design from a text description, no reference audio needed
  • 30 languages plus nine Chinese dialects, no language tag required
  • Apache-2.0 weights and code, with SFT and LoRA fine-tuning support
  • Serving options: Nano-vLLM, vLLM-Omni (OpenAI-style endpoint), GGUF on llama.cpp-omni

Weaknesses

  • Standard install requires CUDA 12.0 or newer and PyTorch 2.5.0 or newer
  • Python support limited to 3.10 through 3.12
  • RTF about 0.3 on RTX 4090 with the default PyTorch path
  • llama.cpp-omni path is slower: RTF about 1.76 on Apple M4 Pro

What it needs

  • GPU required
  • Docker + Compose
  • Needs PyTorch >= 2.5.0, CUDA >= 12.0, Python 3.10-3.12
  • Models: VoxCPM2, VoxCPM1.5, VoxCPM-0.5B, GGUF (llama.cpp-omni)
  • port 8808

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