VoxCPM 1.5

  • Release Date: December 5, 2025

  • Parameter Size: 750M

  • Sampling Rate: 44.1kHz

Note

VoxCPM 1.5 is a legacy release for lighter Chinese/English deployments and existing 1.x workflows.

Overview

We’re thrilled to introduce a major upgrade that improves audio quality and efficiency of VoxCPM, while maintaining the core capabilities of context-aware speech generation and zero-shot voice cloning.

Feature

VoxCPM

VoxCPM1.5

Audio VAE Sampling Rate

16kHz

44.1kHz

LM Token Rate

12.5Hz

6.25Hz

Patch Size

2

4

Token Rate

12.5Hz

6.25Hz

Getting Started

For installation, loading, and the shared generation API, start with Quick Start.

Choose VoxCPM 1.5 when you want a lighter Chinese/English checkpoint than VoxCPM 2 while keeping higher output quality than VoxCPM 1.0.

Model Updates

AudioVAE Sampling Rate: 16kHz -> 44.1kHz

The AudioVAE now supports 44.1kHz sampling rate, which allows the model to:

  • Better cloning fidelity with more preserved high-frequency detail

Note

This upgrade enables higher quality generation when using high-quality reference audio, but does not guarantee that all generated audio will be high-fidelity. The output quality depends on the prompt speech quality.

Token Rate: 12.5Hz -> 6.25Hz

We reduced the token rate in LM from 12.5Hz to 6.25Hz (patch size increased from 2 to 4) while maintaining similar performance on evaluation benchmarks. This change:

  • Reduces computational requirements for generating the same length of audio

  • Provides a foundation for longer audio generation

Migration Guide

From VoxCPM-0.5B to VoxCPM1.5

  1. Update Model Path: Point to VoxCPM1.5 checkpoint

  2. Update Sample Rate: Change sample_rate from 16000 to 44100 in configs

  3. Update Audio Data: The current fine-tuning pipeline automatically resamples to 44.1kHz. If you preprocess offline, resample to 44.1kHz.

  4. Review Training Parameters: Adjust batch size if needed due to higher sampling rate

Backward Compatibility

  • VoxCPM-0.5B models and configurations remain fully supported

  • Code automatically detects and adapts to model version

  • No breaking changes to the API