Qwen/Qwen3-ASR-1.7B-hf

automatic-speech-recognition model by Qwen

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The Qwen3-ASR family includes Qwen3-ASR-1.7B and Qwen3-ASR-0.6B, which support language identification and ASR for 52 languages and dialects. Both leverage large-scale speech training data and the strong audio understanding capability of their foundation model, Qwen3-Omni. The 1.7B version achieves state-of-the-art performance among open-source ASR models and is competitive with the strongest proprietary commercial APIs. Key features: Qwen3-ASR is supported natively in 🤗 Transformers, starting from v5.13.0. applytranscriptionrequest handles chat-template formatting for you and is the recommended entry point. You can force the transcription language as shown below. You can pass free-form context (e.g. domain-specific vocabulary, names, or background information) via prompt to bias the transcription. Pass a list of audio paths and optional languages to transcribe multiple files in one call. Qwen3 ASR also accepts chat template inputs. The applytranscriptionrequest usage above is a convenience wrapper for applychattemplate. The language can be forced through the chat template by prefilling the…

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Model overview

Qwen/Qwen3-ASR-1.7B-hf is a automatic-speech-recognition model repository published by Qwen on Hugging Face. The source reports the transformers library.

This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.

Model facts

Task: automatic-speech-recognition
Library: transformers
Recent downloads (30 days): 302,321
Cumulative likes: 108
Hugging Face trending score: 11
Reported safetensors parameters: 2,038,052,480
Architecture: Qwen3ASRForConditionalGeneration
License: apache-2.0
Access: Not gated by Hugging Face
Created: 2026-06-26T08:34:21.000Z
Last modified: 2026-07-22T11:58:31.000Z

Compatibility and lineage

Reported languages: zh, en, yue, ar, de, fr, es, pt, id, it, ko, ru, th, vi, ja, tr, hi, ms, nl, sv, da, fi, pl, cs, fil, fa, el, hu, mk, ro

Base-model lineage was not included.

Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.

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