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Soniox v4 Real-Time
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Soniox v4 Real-Time is a closed-weights speech-to-text model from Soniox, released February 2026. Licence: proprietary.
Catalogue identity notes
Comparison-only (API retired). Soniox real-time model stt-rt-v4, released February 5, 2026 (Soniox models changelog: 'New models: stt-rt-v4 — Replaces: stt-rt-v3'); 'The stt-rt-v4 model will be removed on June 30, 2026. After June 30, 2026, requests using stt-rt-v4 will automatically route to stt-rt-v5'. Kept because its Pipecat row (run before the retirement) anchors the run.
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 Soniox v4 Real-Time, out of 176 with a score, then more from Soniox.
| # | model | score | where | ||
|---|---|---|---|---|---|
| 8 |  Universal-3.5 Pro | 67±3 | api $0.0035/audio min | ||
| 9 | Soniox v5 Real-Time | 67±3 | api $0.0020/audio min | ||
| 10 | Soniox v4 Real-Time | 67±3 | comparison only | ||
| 11 |  Gemini 3.5 Transcribe | 67±6 | api $0.0050/audio min | ||
| 12 |  Scribe v2 | 66±1 | api $0.0037/audio min | ||
| more from Soniox | |||||
| 6 | Soniox v5 Async | 68±5 | api $0.0017/audio min | ||
see all speech-to-text models · find the ones that fit your machine
$ what it's good at
other tests1 not in a task · 96% of its score
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Pipecat STT Benchmark · pooled semantic WER (1000 smart-turn samples, Sonnet 5.5 judge) | 1.1% ✎ | ▃·▃▅·▅▅·▃▅██ beats 9/16 | 96% |
$ where to run it
No verified API or download recorded yet · add one
$ how the score was worked out · Pipecat STT Benchmark · seman… 96%
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
| source | results | share of the score |
|---|---|---|
 Pipecat STT Benchmark · semantic WER results table (pipecat-ai/stt-benchmark README) | 1 | 96% |
| prior · pull toward the middle | 4% | |
| weighted average | = 66.9 |
$ improve this page
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