Run VibeVoice-ASR-HF Offline on PC No-Internet Version Offline Setup

Run VibeVoice-ASR-HF Offline on PC No-Internet Version Offline Setup

If you want the fastest local installation for this model, use Docker.

Simply follow the directions outlined below.

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1-click setup: the app automatically fetches the large weight files.

There is no manual tuning required; the builder will automatically deploy the best matching configuration.

🔗 SHA sum: 1da9a3d8ecd127d24de40af977d40373 | Updated: 2026-06-28



  • CPU: modern architecture (Zen 3 / Alder Lake minimum)
  • RAM: at least 32 GB in dual-channel mode for bandwidth
  • Disk Space: 80 GB NVMe SSD required for fast model weights loading
  • GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference

The VibeVoice-ASR-HF leverages a transformer-based architecture optimized for low‑latency speech recognition in edge environments. It supports over 100 languages and dialects, delivering real-time transcription with an average word error rate below 5 %. The model achieves sub‑200 ms inference time on standard CPUs, making it suitable for live captioning and voice‑controlled applications. Integrated with popular frameworks through a lightweight API, developers can deploy the model without extensive hardware resources. A comparison of key metrics is provided below.

Parameter Value
Model size ≈ 150 M parameters
Supported languages 100+ languages & dialects
Average latency <200 ms on CPU
Word error rate <5 %
API compatibility REST & gRPC
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