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Tencent Hy-ASR-3.0-preview

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Tencent Hy-ASR-3.0-preview is a closed-weights speech-to-text model from Tencent.

Catalogue identity notes

Exact label 'Tencent Hy-ASR-3.0-preview' as evaluated through its API by the Qwen-Audio team (Table 1 Panel B). Preview API; build/date not stated. Distinct from 'Tencent Cloud ASR' in the report's Table 2.

60.4±4.2comparison only: no current run option verifiedfrom 2 benchmark results across 1 source* thinly tested, treat the rank as provisional

Score within the Open ASR English short-form WER (March 2026) comparison set only.

$ how it compares

The speech-to-text models ranked either side of Tencent Hy-ASR-3.0-preview, out of 176 with a score.

#modelscorewhereRAMreleased
34Granite Speech 4.1 2B Plus IBM61±4local~2.4GB2026-04
35Parakeet TDT 0.6B v2 NVIDIA60±1local~1.9GB2025-05
36Tencent Hy-ASR-3.0-preview Tencent60±4comparison only
37Parakeet Unified EN 0.6B NVIDIA60±4local~0.7GB2026-04
38Grok Voice Transcribe 1.0 xAI60±5comparison only2026-04

see all speech-to-text models · find the ones that fit your machine

$ what it's good at

other tests2 not in a task · 93% of its score
testresultvs the others in its rundifficultycountswhy
Qwen-Audio-3.0-ASR report · Chinese 4-set CER mean (own API runs)2.4% ✎▄········▄·█ beats 2/3avg 6.7%▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 55%sharp
Qwen-Audio-3.0-ASR report · English 3-set WER mean (own API runs)3.2% ✎█···█··█···█ beats 1/3avg 5.6%▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 38%typical

$ where to run it

No verified API or download recorded yet · add one

$ how the score was worked out · Qwen-Audio-3.0-ASR Technical… 93%

Each result implies a score on its own, after adjusting for how hard its test is and who ran it. The score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its counts column above; here it's added up by who ran the tests. How it works

sourceresultsshare of the scorelicence
Qwen-Audio-3.0-ASR Technical Report (arXiv:2609.07549v2)2▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 93%CC BY 4.0
prior · pull toward the middle▇▇ 7%
weighted average= 60.4

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Update model informationAdd a place to run itAdd a test resultPropose a benchmarkCorrect a benchmark scoreEdit data on GitHub

Use a short GitHub form or edit the data through a pull request. Every number needs a source; here's which ones we can use.

data updated · sources and licences · json