Install VoxCPM2 via WebGPU (Browser) with Native FP4

If you want the fastest local installation for this model, use Docker.

Make sure to follow the instructions below.

The client handles the setup, pulling gigabytes of data automatically.

The smart installation system will instantly find the perfect configuration for your specific hardware.

🧮 Hash-code: bb88c317c2d527b9e6cd2dc0e046a462 • 📆 2026-06-24



  • CPU: 8-core / 16-thread recommended for orchestration
  • RAM: high-speed DDR5 memory preferred for CPU offloading
  • Disk Space: free: 80 GB on system drive for scratch space
  • Graphic Processor: hardware Tensor Cores support needed for FP16 acceleration

VoxCPM2 is a next‑generation speech synthesis model designed to generate highly natural‑sounding audio across dozens of languages. It leverages a conditional parameterization approach that reduces memory footprint by up to 60 % while preserving voice fidelity. The architecture integrates a hierarchical encoder and a diffusion‑based decoder, enabling real‑time inference with latency under 150 ms on standard hardware. A built‑in speaker adaptation module allows users to personalize voice models with just a few seconds of audio, eliminating the need for extensive retraining. These capabilities are showcased in a comparative benchmark where VoxCPM2 outperforms prior models on MOS scores, word error rates, and multilingual consistency, as detailed in the table below.

MetricVoxCPM2Prior Model
MOS Score4.624.31
Word Error Rate (%)5.87.4
Multilingual Consistency92%84%

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