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Phonon-1

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Phonon-1 is an open-weights speech-to-text model from Fermion Research, released August 2026. Licence: cc-by-4.0.

Catalogue identity notes

Pinned public model card and documented runtime. No measured runtime memory requirement verified; model file size is not labelled as RAM.

Model information sources

Release date ↗

53.1±6.5comparison 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 Phonon-1, out of 178 with a score, then more from Fermion Research.

#modelscorewhereRAMreleased
94MOSS-Transcribe-Diarize 0.9B OpenMOSS54±4local~1GB2026-07
95GPT-4o Transcribe OpenAI53±1api $0.0060/audio min2025-03
96Phonon-1 Fermion Research53±7comparison only2026-08
97LiteWhisper large-v3-turbo-acc Efficient-Speech (LiteASR)53±4local~2.1GB2025-02
98Voxtral Mini 4B Realtime (2602) Mistral53±2api $0.0060/audio min +local~3.2GB2026-02
more from Fermion Research
73Phonon-2 Fermion Research56±7local~0.7GB2026-09

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

$ what it's good at

other tests1 not in a task · 84% of its score
testresultvs the others in its rundifficultycountswhy
Open ASR seven English sets (Fermion full-set runs) lab6.6% ✎█······█···█ beats 0/2avg 8.4%▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 84%small run

$ where to run it

No verified API or download recorded yet · add one

Official weights and documentation: huggingface.co/FermionResearch ↗

$ how the score was worked out · Phonon-2 model card 84%

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
Phonon-2 model card · lab-reported1cc-by-4.0
prior · pull toward the middle
weighted average= 53.1

$ improve this page

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