If you need a near-instant local setup, just fetch files via a basic curl request.

Use the instructions provided below to complete the setup.

The script takes care of fetching the multi-gigabyte model weights.

To guarantee smooth performance, the process auto-selects the best options.

📊 File Hash: f7b2ecb18490251a36d2f12e7e0026c4 — Last update: 2026-06-29 Verify Processor: 6-core 3.5 GHz minimum required RAM: minimum 16 GB for stable 8B model loading Disk Space: 100 GB for multi-modal model vision components GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference

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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