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LatestOpenBMB1.5
OpenBMBText → Speech

VoxCPM 1.5 Brings Open-Source Voice Cloning

The new 500-million-parameter text-to-speech model from OpenBMB supports both English and Chinese and can replicate a voice from a short audio sample.

Dec 5, 2025
NotableApache 2.0
VoxCPM 1.5

The field of open-source text-to-speech has a new contender with the release of VoxCPM 1.5 by the OpenBMB research group. The model introduces high-quality, zero-shot voice cloning capabilities to the community, enabling users to generate speech in a specific voice using just a short audio sample.

Built on the MiniCPM-4 architecture, VoxCPM 1.5 is a compact 500-million-parameter model. Its relatively small size makes it more accessible for developers and researchers to run and fine-tune on a wider range of hardware, lowering the barrier to entry for creating custom speech applications.

Bilingual Voice Synthesis

A key advantage of the model is its bilingual nature, supporting both English and Chinese within a single framework. This, combined with its permissive Apache 2.0 license, makes it a versatile tool for global applications. Key features include:

  • Zero-shot voice cloning from brief audio clips.
  • Bilingual support for English and Chinese.
  • An efficient 500M parameter architecture.

By providing an open and powerful tool for voice synthesis, OpenBMB is enabling new possibilities in areas like personalized digital assistants, accessible technology, and creative content generation. Developers can explore the model and its capabilities in the official Hugging Face repository.

Sources

  • openbmb/VoxCPM1.5

    Hugging Face

    Visit
OlderMeituan Releases Open, Bilingual Image Editing ModelMeituan · Image Editing · 11 months agoNewerZhipu AI Releases Fast, Open Vision Model GLM-4.6V-FlashZhipu AI · Vision-Language · 11 months ago

Get the model

Hugging Face

Specs

Parameters500M
Sample rate44 kHz
LanguagesEnglish, Chinese
PrecisionBF16
LicenseAPACHE-2.0
Downloads5.4K
Likes364

Can you run it?

Runs on just about anything.

  • BF16 (as published)

    Any modern laptop · 8 GB RAM

    2 GB
  • FP8

    Any modern laptop · 8 GB RAM

    1.5 GB
Your machine
  • Parameter count is an editorial estimate — no weights metadata on Hugging Face.

Estimated from the parameter count. Assumes an 8K context and ~1 GB runtime overhead; actual needs vary. How we estimate


Modalities

Text → Speech

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