Qwen3-ASR-1.7B-GGUF is a quantized version of the Qwen3 automatic speech recognition model. It enables developers to run accurate speech-to-text inference directly on local hardware using GGUF-compatible tools such as llama.cpp or Hugging Face transformers. The repository provides multiple quantization levels for balancing performance and resource usage.
Qwen3 ASR 1.7B is a Voice, TTS & speech product. It focuses on running high-quality automatic speech recognition locally without cloud APIs or expensive GPUs. Qwen3 ASR 1.7B is an open-source project aimed at developers. The project is open source (MIT). The product ships for the web and the command line, and it can be self-hosted.
handy-computer builds and maintains Qwen3 ASR 1.7B, and the product first shipped in 2026. The project is developed in the open on GitHub with 1.4k stars and 419 commits in the last 90 days. PulseGate's similarity index places it among 10 comparable tools. Among its 3 catalogued features are Speech Recognition, GGUF Quantization, and Local Inference.
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