Qwen3-ASR-0.6B-GGUF

unslothai/Qwen3-ASR-0.6B-GGUF

Qwen3-ASR-0.6B-GGUF is a automatic speech recognition model from unslothai. Use it when you need speech turned into text. The card lists the license as apache-2.0.

<p align="center" <img src="https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen3-ASR-Repo/qwen3asrintroduction.png" width="90%"/ <p

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At a glance

Task: Automatic Speech Recognition
License: apache-2.0
Access: Public
Created: Aug 4, 2026
Updated: Oct 22, 2026
SHA: 9045ad9c

Base models

Qwen/Qwen3-ASR-0.6B

Model card

From the Hugging Face model README

Qwen3-ASR

Overview

Introduction

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. Experiments show that the 1.7B version achieves state-of-the-art performance among open-source ASR models and is competitive with the strongest proprietary commercial APIs. Here are the main features:

All-in-one: Qwen3-ASR-1.7B and Qwen3-ASR-0.6B support language identification and speech recognition for 30 languages and 22 Chinese dialects, so as to English accents from multiple countries and regions.
Excellent and Fast: The Qwen3-ASR family ASR models maintains high-quality and robust recognition under complex acoustic environments and challenging text patterns. Qwen3-ASR-1.7B achieves strong performance on both open-sourced and internal benchmarks. While the 0.6B version achieves accuracy-efficient trade-off, it reaches 2000 times throughput at a concurrency of 128. They both achieve streaming / offline unified inference with single model and support transcribe long audio.
Novel and strong forced alignment Solution: We introduce Qwen3-ForcedAligner-0.6B, which supports timestamp prediction for arbitrary units within up to 5 minutes of speech in 11 languages. Evaluations show its timestamp accuracy surpasses E2E based forced-alignment models.
Comprehensive inference toolkit: In addition to open-sourcing the architectures and weights of the Qwen3-ASR series, we also release a powerful, full-featured inference framework that supports vLLM-based batch inference, asynchronous serving, streaming inference, timestamp prediction, and more.

Model Architecture

Released Models Description and Download

Below is an introduction and download information for the Qwen3-ASR models. Please select and download the model that fits your needs.

Model	Supported Languages	Supported Dialects	Inference Mode	Audio Types
Qwen3-ASR-1.7B & Qwen3-ASR-0.6B	Chinese (zh), English (en), Cantonese (yue), Arabic (ar), German (de), French (fr), Spanish (es), Portuguese (pt), Indonesian (id), Italian (it), Korean (ko), Russian (ru), Thai (th), Vietnamese (vi), Japanese (ja), Turkish (tr), Hindi (hi), Malay (ms), Dutch (nl), Swedish (sv), Danish (da), Finnish (fi), Polish (pl), Czech (cs), Filipino (fil), Persian (fa), Greek (el), Hungarian (hu), Macedonian (mk), Romanian (ro)	Anhui, Dongbei, Fujian, Gansu, Guizhou, Hebei, Henan, Hubei, Hunan, Jiangxi, Ningxia, Shandong, Shaanxi, Shanxi, Sichuan, Tianjin, Yunnan, Zhejiang, Cantonese (Hong Kong accent), Cantonese (Guangdong accent), Wu language, Minnan language.	Offline / Streaming	Speech, Singing Voice, Songs with BGM
Qwen3-ForcedAligner-0.6B	Chinese, English, Cantonese, French, German, Italian, Japanese, Korean, Portuguese, Russian, Spanish	--	NAR	Speech

Evaluation

During evaluation, we ran inference for all models with dtype=torch.bfloat16 and set max_new_tokens=1024 using vLLM. Greedy search was used for all decoding, and none of the tests specified a language parameter. The detailed evaluation results are shown below.

<details> <summary>ASR Benchmarks on Public Datasets (WER ↓)</summary> <table> <thead> <tr> <th colspan="2" style="text-align: left;"></th> <th style="text-align: center;">GPT-4o -Transcribe</th> <th style="text-align: center;">Gemini-2.5 -Pro</th> <th style="text-align: center;">Doubao-ASR</th> <th style="text-align: center;">Whisper -large-v3</th> <th style="text-align: center;">Fun-ASR -MLT-Nano</th> <th style="text-align: center;">Qwen3-ASR -0.6B</th> <th style="text-align: center;">Qwen3-ASR -1.7B</th> </tr> </thead> <tbody> <tr> <td colspan="9" style="text-align: left; font-style: italic; border-top: 1px solid #ddd; border-bottom: 1px solid #ddd;">English (en)</td> </tr> <tr> <td colspan="2" style="text-align: left;">Librispeech clean | other</td> <td style="text-align: center;">1.39 | 3.75</td> <td style="text-align: center;">2.89 | 3.56</td> <td style="text-align: center;">2.78 | 5.70</td> <td style="text-align: center;">1.51 | 3.97</td> <td style="text-align: center;">1.68 | 4.03</td> <td style="text-align: center;">2.11 | 4.55</td> <td style="text-align: center;">1.63 | 3.38</td> </tr> <tr> <td colspan="2" style="text-align: left;">GigaSpeech</td> <td style="text-align: center;">25.50</td> <td style="text-align: center;">9.37</td> <td style="text-align: center;">9.55</td> <td style="text-align: center;">9.76</td> <td style="text-align: center;">-</td> <td style="text-align: center;">8.88</td> <td style="text-align: center;">8.45</td> </tr> <tr> <td colspan="2" style="text-align: left;">CV-en</td> <td style="text-align: center;">9.08</td> <td style="text-align: center;">14.49</td> <td style="text-align: center;">13.78</td> <td style="text-align: center;">9.90</td> <td style="text-align: center;">9.90</td> <td style="text-align: center;">9.92</td> <td style="text-align: center;">7.39</td> </tr> <tr> <td colspan="2" style="text-align: left;">Fleurs-en</td> <td style="text-align: center;">2.40</td> <td style="text-align: center;">2.94</td> <td style="text-align: center;">6.31</td> <td style="text-align: center;">4.08</td> <td style="text-align: center;">5.49</td> <td style="text-align: center;">4.39</td> <td style="text-align: center;">3.35</td> </tr> <tr> <td colspan="2" style="text-align: left;">MLS-en</td> <td style="text-align: center;">5.12</td> <td style="text-align: center;">3.68</td> <td style="text-align: center;">7.09</td> <td style="text-align: center;">4.87</td> <td style="text-align: center;">-</td> <td style="text-align: center;">6.00</td> <td style="text-align: center;">4.58</td> </tr> <tr> <td colspan="2" style="text-align: left;">Tedlium</td> <td style="text-align: center;">7.69</td> <td style="text-align: center;">6.15</td> <td style="text-align: center;">4.91</td> <td style="text-align: center;">6.84</td> <td style="text-align: center;">-</td> <td style="text-align: center;">3.85</td> <td style="text-align: center;">4.50</td> </tr> <tr> <td colspan="2" style="text-align: left;">VoxPopuli</td> <td style="text-align: center;">10.29</td> <td style="text-align: center;">11.36</td> <td style="text-align: center;">12.12</td> <td style="text-align: center;">12.05</td> <td style="text-align: center;">-</td> <td style="text-align: center;">9.96</td> <td style="text-align: center;">9.15</td> </tr> <tr> <td colspan="9" style="text-align: left; font-style: italic; border-top: 1px solid #ddd; border-bottom: 1px solid #ddd;">Chinese (zh)</td> </tr> <tr> <td colspan="2" style="text-align: left;">WenetSpeech net | meeting</td> <td style="text-align: center;">15.30 | 32.27</td> <td style="text-align: center;">14.43 | 13.47</td> <td style="text-align: center;">N/A</td> <td style="text-align: center;">9.86 | 19.11</td> <td style="text-align: center;">6.35 | -</td> <td style="text-align: center;">5.97 | 6.88</td> <td style="text-align: center;">4.97 | 5.88</td> </tr> <tr> <td colspan="2" style="text-align: left;">AISHELL-2-test</td> <td style="text-align: center;">4.24</td> <td style="text-align: center;">11.62</td> <td style="text-align: center;">2.85</td> <td style="text-align: center;">5.06</td> <td style="text-align: center;">-</td> <td style="text-align: center;">3.15</td> <td style="text-align: center;">2.71</td> </tr> <tr> <td colspan="2" style="text-align: left;">SpeechIO</td> <td style="text-align: center;">12.86</td> <td style="text-align: center;">5.30</td> <td style="text-align: center;">2.93</td> <td style="text-align: center;">7.56</td> <td style="text-align: center;">-</td> <td style="text-align: center;">3.44</td> <td style="text-align: center;">2.88</td> </tr> <tr> <td colspan="2" style="text-align: left;">Fleurs-zh</td> <td style="text-align: center;">2.44</td> <td style="text-align: center;">2.71</td> <td style="text-align: center;">2.69</td> <td style="text-align: center;">4.09</td> <td style="text-align: center;">3.51</td> <td style="text-align: center;">2.88</td> <td style="text-align: center;">2.41</td> </tr> <tr> <td colspan="2" style="text-align: left;">CV-zh</td> <td style="text-align: center;">6.32</td> <td style="text-align: center;">7.70</td> <td style="text-align: center;">5.95</td> <td style="text-align: center;">12.91</td> <td style="text-align: center;">6.20</td> <td style="text-align: center;">6.89</td> <td style="text-align: center;">5.35</td> </tr> <tr> <td colspan="9" style="text-align: left; font-style: italic; border-top: 1px solid #ddd; border-bottom: 1px solid #ddd;">Chinese Dialect</td> </tr> <tr> <td colspan="2" style="text-align: left;">KeSpeech</td> <td style="text-align: center;">26.87</td> <td style="text-align: center;">24.71</td> <td style="text-align: center;">5.27</td> <td style="text-align: center;">28.79</td> <td style="text-align: center;">-</td> <td style="text-align: center;">7.08</td> <td style="text-align: center;">5.10</td> </tr> <tr> <td colspan="2" style="text-align: left;">Fleurs-yue</td> <td style="text-align: center;">4.98</td> <td style="text-align: center;">9.43</td> <td style="text-align: center;">4.98</td> <td style="text-align: center;">9.18</td> <td style="text-align: center;">-</td> <td style="text-align: center;">5.79</td> <td style="text-align: center;">3.98</td> </tr> <tr> <td colspan="2" style="text-align: left;">CV-yue</td> <td style="text-align: center;">11.36</td> <td style="text-align: center;">18.76</td> <td style="text-align: center;">13.20</td> <td style="text-align: center;">16.23</td> <td style="text-align: center;">-</td> <td style="text-align: center;">9.50</td> <td style="text-align: center;">7.57</td> </tr> <tr> <td colspan="2" style="text-align: left;">CV-zh-tw</td> <td style="text-align: center;">6.32</td> <td style="text-align: center;">7.31</td> <td style="text-align: center;">4.06</td> <td style="text-align: center;">7.84</td> <td style="text-align: center;">-</td> <td style="text-align: center;">5.59</td> <td style="text-align: center;">3.77</td> </tr> <tr> <td colspan="2" style="text-align: left;">WenetSpeech-Yue short | long</td> <td style="text-align: center;">15.62 | 25.29</td> <td style="text-align: center;">25.19 | 11.23</td> <td style="text-align: center;">9.74 | 11.40</td> <td style="text-align: center;">32.26 | 46.64</td> <td style="text-align: center;">- | -</td> <td style="text-align: center;">7.54 | 9.92</td> <td style="text-align: center;">5.82 | 8.85</td> </tr> <tr> <td colspan="2" style="text-align: left;">WenetSpeech-Chuan easy | hard</td> <td style="text-align: center;">34.81 | 53.98</td> <td style="text-align: center;">43.79 | 67.30</td> <td style="text-align: center;">11.40 | 20.20</td> <td style="text-align: center;">14.35 | 26.80</td> <td style="text-align: center;">- | -</td> <td style="text-align: center;">13.92 | 24.45</td> <td style="text-align: center;">11.99 | 21.63</td> </tr> </tbody> </table> </details> <details> <summary>ASR Benchmarks on Internal Datasets (WER ↓)</summary> <table> <thead> <tr> <th style="text-align: left;"></th> <th style="text-align: center;">GPT-4o -Transcribe</th> <th style="text-align: center;">Gemini-2.5 -Pro</th> <th style="text-align: center;">Doubao-ASR</th> <th style="text-align: center;">Whisper -large-v3</th> <th style="text-align: center;">Fun-ASR -MLT-Nano</th> <th style="text-align: center;">Qwen3-ASR -0.6B</th> <th style="text-align: center;">Qwen3-ASR -1.7B</th> </tr> </thead> <tbody> <tr> <td colspan="8" style="text-align: left; font-style: italic; border-top: 1px solid #ddd; border-bottom: 1px solid #ddd;">Accented English</td> </tr> <tr> <td style="text-align: left;">Dialog-Accented English</td> <td style="text-align: center;">28.56</td> <td style="text-align: center;">23.85</td> <td style="text-align: center;">20.41</td> <td style="text-align: center;">21.30</td> <td style="text-align: center;">19.96</td> <td style="text-align: center;">16.62</td> <td style="text-align: center;">16.07</td> </tr> <tr> <td colspan="8" style="text-align: left; font-style: italic; border-top: 1px solid #ddd; border-bottom: 1px solid #ddd;">Chinese Mandarin</td> </tr> <tr> <td style="text-align: left;">Elders&Kids</td> <td style="text-align: center;">14.27</td> <td style="text-align: center;">36.93</td> <td style="text-align: center;">4.17</td> <td style="text-align: center;">10.61</td> <td style="text-align: center;">4.54</td> <td style="text-align: center;">4.48</td> <td style="text-align: center;">3.81</td> </tr> <tr> <td style="text-align: left;">ExtremeNoise</td> <td style="text-align: center;">36.11</td> <td style="text-align: center;">29.06</td> <td style="text-align: center;">17.04</td> <td style="text-align: center;">63.17</td> <td style="text-align: center;">36.55</td> <td style="text-align: center;">17.88</td> <td style="text-align: center;">16.17</td> </tr> <tr> <td style="text-align: left;">TongueTwister</td> <td style="text-align: center;">20.87</td> <td style="text-align: center;">4.97</td> <td style="text-align: center;">3.47</td> <td style="text-align: center;">16.63</td> <td style="text-align: center;">9.02</td> <td style="text-align: center;">4.06</td> <td style="text-align: center;">2.44</td> </tr> <tr> <td style="text-align: left;">Dialog-Mandarin</td> <td style="text-align: center;">20.73</td> <td style="text-align: center;">12.50</td> <td style="text-align: center;">6.61</td> <td style="text-align: center;">14.01</td> <td style="text-align: center;">7.32</td> <td style="text-align: center;">7.06</td> <td style="text-align: center;">6.54</td> </tr> <tr> <td colspan="8" style="text-align: left; font-style: italic; border-top: 1px solid #ddd; border-bottom: 1px solid #ddd;">Chinese Dialect</td> </tr> <tr> <td style="text-align: left;">Dialog-Cantonese</td> <td style="text-align: center;">16.05</td> <td style="text-align: center;">14.98</td> <td style="text-align: center;">7.56</td> <td style="text-align: center;">31.04</td> <td style="text-align: center;">5.85</td> <td style="text-align: center;">4.80</td> <td style="text-align: center;">4.12</td> </tr> <tr> <td style="text-align: left;">Dialog-Chinese Dialects</td> <td style="text-align: center;">45.37</td> <td style="text-align: center;">47.70</td> <td style="text-align: center;">19.85</td> <td style="text-align: center;">44.55</td> <td style="text-align: center;">19.41</td> <td style="text-align: center;">18.24</td> <td style="text-align: center;">15.94</td> </tr> </tbody> </table> Dialect coverage: Results for Dialog-Accented English are averaged over 16 accents, and results for Dialog-Chinese Dialects are averaged over 22 Chinese dialects. </details> <details> <summary>Multilingual ASR Benchmarks (WER ↓)</summary> <table> <thead> <tr> <th style="text-align: left;"></th> <th style="text-align: center;">GLM-ASR -Nano-2512</th> <th style="text-align: center;">Whisper -large-v3</th> <th style="text-align: center;">Fun-ASR -MLT-Nano</th> <th style="text-align: center;">Qwen3-ASR -0.6B</th> <th style="text-align: center;">Qwen3-ASR -1.7B</th> </tr> </thead> <tbody> <tr> <td colspan="6" style="text-align: left; font-style: italic; border-top: 1px solid #ddd; border-bottom: 1px solid #ddd;">Open-sourced Benchmarks</td> </tr> <tr> <td style="text-align: left;">MLS</td> <td style="text-align: center;">13.32</td> <td style="text-align: center;">8.62</td> <td style="text-align: center;">28.70</td> <td style="text-align: center;">13.19</td> <td style="text-align: center;">8.55</td> </tr> <tr> <td style="text-align: left;">CommonVoice</td> <td style="text-align: center;">19.40</td> <td style="text-align: center;">10.77</td> <td style="text-align: center;">17.25</td> <td style="text-align: center;">12.75</td> <td style="text-align: center;">9.18</td> </tr> <tr> <td style="text-align: left;">MLC-SLM</td> <td style="text-align: center;">34.93</td> <td style="text-align: center;">15.68</td> <td style="text-align: center;">29.94</td> <td style="text-align: center;">15.84</td> <td style="text-align: center;">12.74</td> </tr> <tr> <td style="text-align: left;">Fleurs</td> <td style="text-align: center;">16.08</td> <td style="text-align: center;">5.27</td> <td style="text-align: center;">10.03</td> <td style="text-align: center;">7.57</td> <td style="text-align: center;">4.90</td> </tr> <tr> <td style="text-align: left;">Fleurs†</td> <td style="text-align: center;">20.05</td> <td style="text-align: center;">6.85</td> <td style="text-align: center;">31.89</td> <td style="text-align: center;">10.37</td> <td style="text-align: center;">6.62</td> </tr> <tr> <td style="text-align: left;">Fleurs††</td> <td style="text-align: center;">24.83</td> <td style="text-align: center;">8.16</td> <td style="text-align: center;">47.84</td> <td style="text-align: center;">21.80</td> <td style="text-align: center;">12.60</td> </tr> <tr> <td colspan="6" style="text-align: left; font-style: italic; border-top: 1px solid #ddd; border-bottom: 1px solid #ddd;">Qwen-ASR Internal Benchmarks</td> </tr> <tr> <td style="text-align: left;">News-Multilingual</td> <td style="text-align: center;">49.40</td> <td style="text-align: center;">14.80</td> <td style="text-align: center;">65.07</td> <td style="text-align: center;">17.39</td> <td style="text-align: center;">12.80</td> </tr> </tbody> </table> Language coverage: MLS includes 8 languages: {da, de, en, es, fr, it, pl, pt}. CommonVoice includes 13 languages: {en, zh, yue, zh_TW, ar, de, es, fr, it, ja, ko, pt, ru}. MLC-SLM includes 11 languages: {en, fr, de, it, pt, es, ja, ko, ru, th, vi}. Fleurs includes 12 languages: {en, zh, yue, ar, de, es, fr, it, ja, ko, pt, ru }. Fleurs† includes 8 additional languages beyond Fleurs: {hi, id, ms, nl, pl, th, tr, vi}. Fleurs†† includes 10 additional languages beyond Fleurs†: {cs, da, el, fa, fi, fil, hu, mk, ro, sv}. News-Multilingual includes 15 languages: {ar, de, es, fr, hi, id, it, ja, ko, nl, pl, pt, ru, th, vi}. </details> <details> <summary>Language Identification Accuracy (%) ↑</summary> <table> <thead> <tr> <th style="text-align: left;"></th> <th style="text-align: center;">Whisper-large-v3</th> <th style="text-align: center;">Qwen3-ASR-0.6B</th> <th style="text-align: center;">Qwen3-ASR-1.7B</th> </tr> </thead> <tbody> <tr> <td style="text-align: left;">MLS</td> <td style="text-align: center;">99.9</td> <td style="text-align: center;">99.3</td> <td style="text-align: center;">99.9</td> </tr> <tr> <td style="text-align: left;">CommonVoice</td> <td style="text-align: center;">92.7</td> <td style="text-align: center;">98.2</td> <td style="text-align: center;">98.7</td> </tr> <tr> <td style="text-align: left;">MLC-SLM</td> <td style="text-align: center;">89.2</td> <td style="text-align: center;">92.7</td> <td style="text-align: center;">94.1</td> </tr> <tr> <td style="text-align: left;">Fleurs</td> <td style="text-align: center;">94.6</td> <td style="text-align: center;">97.1</td> <td style="text-align: center;">98.7</td> </tr> <tr style="border-top: 1px solid #ddd;"> <td style="text-align: left;">Avg.</td> <td style="text-align: center;">94.1</td> <td style="text-align: center;">96.8</td> <td style="text-align: center;">97.9</td> </tr> </tbody> </table> Language coverage: The language sets follow Multilingual ASR Benchmarks. Here, Fleurs corresponds to Fleurs†† in Multilingual ASR Benchmarks and covers 30 languages. </details> <details> <summary>Singing Voice & Song Transcription (WER ↓)</summary> <table> <thead> <tr> <th style="text-align: left;"></th> <th style="text-align: center;">GPT-4o -Transcribe</th> <th style="text-align: center;">Gemini-2.5 -Pro</th> <th style="text-align: center;">Doubao-ASR -1.0</th> <th style="text-align: center;">Whisper -large-v3</th> <th style="text-align: center;">Fun-ASR-MLT -Nano</th> <th style="text-align: center;">Qwen3-ASR -1.7B</th> </tr> </thead> <tbody> <tr> <td colspan="7" style="text-align: left; font-style: italic; border-top: 1px solid #ddd; border-bottom: 1px solid #ddd;">Singing</td> </tr> <tr> <td style="text-align: left;">M4Singer</td> <td style="text-align: center;">16.77</td> <td style="text-align: center;">20.88</td> <td style="text-align: center;">7.88</td> <td style="text-align: center;">13.58</td> <td style="text-align: center;">7.29</td> <td style="text-align: center;">5.98</td> </tr> <tr> <td style="text-align: left;">MIR-1k-vocal</td> <td style="text-align: center;">11.87</td> <td style="text-align: center;">9.85</td> <td style="text-align: center;">6.56</td> <td style="text-align: center;">11.71</td> <td style="text-align: center;">8.17</td> <td style="text-align: center;">6.25</td> </tr> <tr> <td style="text-align: left;">Opencpop</td> <td style="text-align: center;">7.93</td> <td style="text-align: center;">6.49</td> <td style="text-align: center;">3.80</td> <td style="text-align: center;">9.52</td> <td style="text-align: center;">2.98</td> <td style="text-align: center;">3.08</td> </tr> <tr> <td style="text-align: left;">Popcs</td> <td style="text-align: center;">32.84</td> <td style="text-align: center;">15.13</td> <td style="text-align: center;">8.97</td> <td style="text-align: center;">13.77</td> <td style="text-align: center;">9.42</td> <td style="text-align: center;">8.52</td> </tr> <tr> <td colspan="7" style="text-align: left; font-style: italic; border-top: 1px solid #ddd; border-bottom: 1px solid #ddd;">Songs with BGM</td> </tr> <tr> <td style="text-align: left;">EntireSongs-en</td> <td style="text-align: center;">30.71</td> <td style="text-align: center;">12.18</td> <td style="text-align: center;">33.51</td> <td style="text-align: center;">N/A</td> <td style="text-align: center;">N/A</td> <td style="text-align: center;">14.60</td> </tr> <tr> <td style="text-align: left;">EntireSongs-zh</td> <td style="text-align: center;">34.86</td> <td style="text-align: center;">18.68</td> <td style="text-align: center;">23.99</td> <td style="text-align: center;">N/A</td> <td style="text-align: center;">N/A</td> <td style="text-align: center;">13.91</td> </tr> </tbody> </table> </details> <details> <summary>ASR Inference Mode Performance (WER ↓)</summary> <table> <thead> <tr> <th style="text-align: left;">Model</th> <th style="text-align: left;">Infer. Mode</th> <th style="text-align: center;">Librispeech</th> <th style="text-align: center;">Fleurs-en</th> <th style="text-align: center;">Fleurs-zh</th> <th style="text-align: center;">Avg.</th> </tr> </thead> <tbody> <tr> <td rowspan="2" style="text-align: left; vertical-align: middle;">Qwen3-ASR-1.7B</td> <td style="text-align: left;">Offline</td> <td style="text-align: center;">1.63 | 3.38</td> <td style="text-align: center;">3.35</td> <td style="text-align: center;">2.41</td> <td style="text-align: center;">2.69</td> </tr> <tr> <td style="text-align: left;">Streaming</td> <td style="text-align: center;">1.95 | 4.51</td> <td style="text-align: center;">4.02</td> <td style="text-align: center;">2.84</td> <td style="text-align: center;">3.33</td> </tr> <tr style="border-top: 1px solid #ddd;"> <td rowspan="2" style="text-align: left; vertical-align: middle;">Qwen3-ASR-0.6B</td> <td style="text-align: left;">Offline</td> <td style="text-align: center;">2.11 | 4.55</td> <td style="text-align: center;">4.39</td> <td style="text-align: center;">2.88</td> <td style="text-align: center;">3.48</td> </tr> <tr> <td style="text-align: left;">Streaming</td> <td style="text-align: center;">2.54 | 6.27</td> <td style="text-align: center;">5.38</td> <td style="text-align: center;">3.40</td> <td style="text-align: center;">4.40</td> </tr> </tbody> </table> </details> <details> <summary>Forced Alignment Benchmarks (AAS ms ↓)</summary> <table> <thead> <tr> <th style="text-align: left;"></th> <th style="text-align: center;">Monotonic-Aligner</th> <th style="text-align: center;">NFA</th> <th style="text-align: center;">WhisperX</th> <th style="text-align: center;">Qwen3-ForcedAligner-0.6B</th> </tr> </thead> <tbody> <tr> <td colspan="5" style="text-align: left; font-style: italic; border-top: 1px solid #ddd; border-bottom: 1px solid #ddd;">MFA-Labeled Raw</td> </tr> <tr> <td style="text-align: left;">Chinese</td> <td style="text-align: center;">161.1</td> <td style="text-align: center;">109.8</td> <td style="text-align: center;">-</td> <td style="text-align: center;">33.1</td> </tr> <tr> <td style="text-align: left;">English</td> <td style="text-align: center;">-</td> <td style="text-align: center;">107.5</td> <td style="text-align: center;">92.1</td> <td style="text-align: center;">37.5</td> </tr> <tr> <td style="text-align: left;">French</td> <td style="text-align: center;">-</td> <td style="text-align: center;">100.7</td> <td style="text-align: center;">145.3</td> <td style="text-align: center;">41.7</td> </tr> <tr> <td style="text-align: left;">German</td> <td style="text-align: center;">-</td> <td style="text-align: center;">122.7</td> <td style="text-align: center;">165.1</td> <td style="text-align: center;">46.5</td> </tr> <tr> <td style="text-align: left;">Italian</td> <td style="text-align: center;">-</td> <td style="text-align: center;">142.7</td> <td style="text-align: center;">155.5</td> <td style="text-align: center;">75.5</td> </tr> <tr> <td style="text-align: left;">Japanese</td> <td style="text-align: center;">-</td> <td style="text-align: center;">-</td> <td style="text-align: center;">-</td> <td style="text-align: center;">42.2</td> </tr> <tr> <td style="text-align: left;">Korean</td> <td style="text-align: center;">-</td> <td style="text-align: center;">-</td> <td style="text-align: center;">-</td> <td style="text-align: center;">37.2</td> </tr> <tr> <td style="text-align: left;">Portuguese</td> <td style="text-align: center;">-</td> <td style="text-align: center;">-</td> <td style="text-align: center;">-</td> <td style="text-align: center;">38.4</td> </tr> <tr> <td style="text-align: left;">Russian</td> <td style="text-align: center;">-</td> <td style="text-align: center;">200.7</td> <td style="text-align: center;">-</td> <td style="text-align: center;">40.2</td> </tr> <tr> <td style="text-align: left;">Spanish</td> <td style="text-align: center;">-</td> <td style="text-align: center;">124.7</td> <td style="text-align: center;">108.0</td> <td style="text-align: center;">36.8</td> </tr> <tr> <td style="text-align: left;">Avg.</td> <td style="text-align: center;">161.1</td> <td style="text-align: center;">129.8</td> <td style="text-align: center;">133.2</td> <td style="text-align: center;">42.9</td> </tr> <tr> <td colspan="5" style="text-align: left; font-style: italic; border-top: 1px solid #ddd; border-bottom: 1px solid #ddd;">MFA-Labeled Concat-300s</td> </tr> <tr> <td style="text-align: left;">Chinese</td> <td style="text-align: center;">1742.4</td> <td style="text-align: center;">235.0</td> <td style="text-align: center;">-</td> <td style="text-align: center;">36.5</td> </tr> <tr> <td style="text-align: left;">English</td> <td style="text-align: center;">-</td> <td style="text-align: center;">226.7</td> <td style="text-align: center;">227.2</td> <td style="text-align: center;">58.6</td> </tr> <tr> <td style="text-align: left;">French</td> <td style="text-align: center;">-</td> <td style="text-align: center;">230.6</td> <td style="text-align: center;">2052.2</td> <td style="text-align: center;">53.4</td> </tr> <tr> <td style="text-align: left;">German</td> <td style="text-align: center;">-</td> <td style="text-align: center;">220.3</td> <td style="text-align: center;">993.4</td> <td style="text-align: center;">62.4</td> </tr> <tr> <td style="text-align: left;">Italian</td> <td style="text-align: center;">-</td> <td style="text-align: center;">290.5</td> <td style="text-align: center;">5719.4</td> <td style="text-align: center;">81.6</td> </tr> <tr> <td style="text-align: left;">Japanese</td> <td style="text-align: center;">-</td> <td style="text-align: center;">-</td> <td style="text-align: center;">-</td> <td style="text-align: center;">81.3</td> </tr> <tr> <td style="text-align: left;">Korean</td> <td style="text-align: center;">-</td> <td style="text-align: center;">-</td> <td style="text-align: center;">-</td> <td style="text-align: center;">42.2</td> </tr> <tr> <td style="text-align: left;">Portuguese</td> <td style="text-align: center;">-</td> <td style="text-align: center;">-</td> <td style="text-align: center;">-</td> <td style="text-align: center;">50.0</td> </tr> <tr> <td style="text-align: left;">Russian</td> <td style="text-align: center;">-</td> <td style="text-align: center;">283.3</td> <td style="text-align: center;">-</td> <td style="text-align: center;">43.0</td> </tr> <tr> <td style="text-align: left;">Spanish</td> <td style="text-align: center;">-</td> <td style="text-align: center;">240.2</td> <td style="text-align: center;">4549.9</td> <td style="text-align: center;">39.6</td> </tr> <tr> <td style="text-align: left;">Cross-lingual</td> <td style="text-align: center;">-</td> <td style="text-align: center;">-</td> <td style="text-align: center;">-</td> <td style="text-align: center;">34.2</td> </tr> <tr> <td style="text-align: left;">Avg.</td> <td style="text-align: center;">1742.4</td> <td style="text-align: center;">246.7</td> <td style="text-align: center;">2708.4</td> <td style="text-align: center;">52.9</td> </tr> <tr> <td colspan="5" style="text-align: left; font-style: italic; border-top: 1px solid #ddd; border-bottom: 1px solid #ddd;">Human-Labeled</td> </tr> <tr> <td style="text-align: left;">Raw</td> <td style="text-align: center;">49.9</td> <td style="text-align: center;">88.6</td> <td style="text-align: center;">-</td> <td style="text-align: center;">27.8</td> </tr> <tr> <td style="text-align: left;">Raw-Noisy</td> <td style="text-align: center;">53.3</td> <td style="text-align: center;">89.5</td> <td style="text-align: center;">-</td> <td style="text-align: center;">41.8</td> </tr> <tr> <td style="text-align: left;">Concat-60s</td> <td style="text-align: center;">51.1</td> <td style="text-align: center;">86.7</td> <td style="text-align: center;">-</td> <td style="text-align: center;">25.3</td> </tr> <tr> <td style="text-align: left;">Concat-300s</td> <td style="text-align: center;">410.8</td> <td style="text-align: center;">140.0</td> <td style="text-align: center;">-</td> <td style="text-align: center;">24.8</td> </tr> <tr> <td style="text-align: left;">Concat-Cross-lingual</td> <td style="text-align: center;">-</td> <td style="text-align: center;">-</td> <td style="text-align: center;">-</td> <td style="text-align: center;">42.5</td> </tr> <tr> <td style="text-align: left;">Avg.</td> <td style="text-align: center;">141.3</td> <td style="text-align: center;">101.2</td> <td style="text-align: center;">-</td> <td style="text-align: center;">32.4</td> </tr> </tbody> </table> </details>

Citation

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@article{Qwen3-ASR,
  title={Qwen3-ASR Technical Report},
  author={Xian Shi, Xiong Wang, Zhifang Guo, Yongqi Wang, Pei Zhang, Xinyu Zhang, Zishan Guo, Hongkun Hao, Yu Xi, Baosong Yang, Jin Xu, Jingren Zhou, Junyang Lin},
  journal={arXiv preprint arXiv:2601.21337},
  year={2026}
}

Task: Automatic Speech Recognition
License: apache-2.0
Created: Aug 4, 2026
Updated: Oct 22, 2026