VoxCPM2 Using Pinokio Windows

Running this model locally is fastest when deployed through a PowerShell script.

Please follow the instructions listed below to get started.

Everything happens automatically, including the heavy cloud asset download.

There is no manual tuning required; the builder deploys the best matching configuration.

🔒 Hash checksum: af4eaa672f582ff0316e86f27f767b63 • 📆 Last updated: 2026-07-01



  • Processor: next-gen chip for heavy context processing
  • RAM: high-speed DDR5 memory preferred for CPU offloading
  • Disk Space: 80 GB NVMe SSD required for fast model weights loading
  • GPU: high memory bandwidth GPU for next-gen local AI pipeline

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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