VibeVoice-ASR-HF PC with NPU Quantized GGUF Windows

For an instant local deployment, running a pre-configured shell script is ideal.

Execute the commands and steps outlined below.

The tool automatically synchronizes and downloads the model database.

The configuration wizard runs silently to set up the model for peak performance.

📊 File Hash: 58d599d1ee563f242eea83ac70216d38 — Last update: 2026-06-27 Verify CPU: modern architecture (Zen 3 / Alder Lake minimum) RAM: high-speed DDR5 memory preferred for CPU offloading Disk Space: at least 100 GB for multiple local LLM variants 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.

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