whatmodel.sh / stt / Zipformer Transducer XL 290M

Zipformer Transducer XL 290M

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Zipformer Transducer XL 290M is an open-weights speech-to-text model from SoundsGood AI, released May 2026. Its published size is 0.288B parameters. Licence: cc-by-nc-4.0.

Catalogue identity notes

Exact checkpoint soundsgoodai/Zipformer-transducer-XL-290M (k2/Icefall). Weights CC-BY-NC-4.0. Params: card (288M). No local variant: the card's usage needs an Icefall checkout plus k2 and 20+ architecture flags, not a single copy-pasteable command.

56.3±5.1comparison only: no current run option verifiedfrom 1 benchmark result 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 Zipformer Transducer XL 290M, out of 176 with a score.

#modelscorewhereRAMreleased
70Rev AI Fusion (Whisper Fusion) Rev57±4comparison only2024-01
71Orukeet Oruk AI57±4local~0.7GB2026-09
72Zipformer Transducer XL 290M SoundsGood AI56±5comparison only2026-05
73Parakeet TDT-CTC 1.1B NVIDIA56±4local~1.3GB2024-05
74GPT-4o Mini Transcribe OpenAI56±2api $0.0030/audio min2025-03

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

$ what it's good at

other tests1 not in a task · 90% of its score
testresultvs the others in its rundifficultycountswhy
Open ASR English short-form WER (March 2026) lab6.8% ✎▁▁▁▃··▁▁▂██▆ beats 64/86avg 8.2%▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 90%blunt

$ where to run it

No verified API or download recorded yet · add one

Official weights and documentation: huggingface.co/soundsgoodai ↗

$ how the score was worked out · Open ASR Leaderboard 90%

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
Open ASR Leaderboard · lab-reported1▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 90%Apache-2.0
prior · pull toward the middle▇▇▇ 10%
weighted average= 56.3

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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