The fastest way to get this model running locally is via Docker.

Use the instructions provided below to complete the setup.

Hands-free setup: the system self-downloads the heavy model files.

To guarantee smooth performance, the installation process auto-selects the best possible options for your PC.

💾 File hash: 5f3fb62dc78b7fea77a2ff2907a9dbf9 (Update date: 2026-06-22) Verify Processor: 4.0 GHz+ boost clock recommended for CPU inference RAM: enough space for background apps and OS overhead Disk Space: 100 GB for multi-modal model vision components GPU: modern architecture (Ada Lovelace / Ampere minimum)

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.

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