VoxCPM2 Locally via Ollama 2

VoxCPM2 Locally via Ollama 2

Deploying this model locally is quickest when done via a simple curl command.

Follow the guidelines below to continue.

The installer auto-downloads and deploys the entire model pack.

The automated script takes care of everything, tailoring the setup to your specs.

📘 Build Hash: 1434b2ececd0bde2fcacdfc74f83c69f • 🗓 2026-06-26
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  • Processor: 6-core 3.5 GHz minimum required
  • RAM: 48 GB needed to prevent memory swapping to disk
  • 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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