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Quick Run VoxCPM2 Using Pinokio One-Click Setup Offline Setup

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Quick Run VoxCPM2 Using Pinokio One-Click Setup Offline Setup

To install this model locally in the shortest time, opt for Docker.

Please follow the instructions listed below to get started.

The loader auto-caches the model archive (several GBs included).

During setup, the script automatically determines and applies the best settings tailored to your machine.

📎 HASH: 7c018eda8118f40de64f43c9e81d0ecf | Updated: 2026-06-24



  • CPU: modern architecture (Zen 3 / Alder Lake minimum)
  • RAM: enough space for background apps and OS overhead
  • Disk: high-speed SSD 120 GB to cache model layers
  • 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.

Metric VoxCPM2 Prior Model
MOS Score 4.62 4.31
Word Error Rate (%) 5.8 7.4
Multilingual Consistency 92% 84%
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