Scribe v1
Zoom
Speech to textTranscribes a recording into words
- Type
- Proprietary
- Input
- None held
- Output
- None held
- Cached
- None held
We don't hold a list price for this model yet · hosted only — no weights published
Our take
Written Aug 2, 2026Scribe v1 is Zoom's proprietary speech-to-text model, available only through ElevenLabs, that turns English audio into written text. It is accurate on clean read-aloud recordings but its error rate rises sharply on accented speech, meetings and podcasts.
Pick this for high-quality transcription of clean, scripted English audio where the recording is good. Use it for budget-conscious English speech-to-text work via ElevenLabs. Skip it if your audio is accented, multi-speaker, or from meetings or podcasts, or if you need any language other than English.
The case for it
- Strong on clean read-aloud English, with about one word in ninety wrong, and similarly low error rates on financial calls and harder read speech.
- Input cost at ElevenLabs is extremely low for the speech-to-text category.
The case against it
- Accuracy collapses on challenging real-world audio: the error rate jumps more than eightfold from clean read-aloud to accented speech, and more than sixfold to podcasts, video and meetings.
- Only one language is supported, and every accuracy figure we hold is English-only.
- A single provider offer with no open weights or alternative hosts, so there is no portability if terms or pricing change.
How good is it?
TranscriptionTurning speech into text4.5 of 5Open ASR WER · 8th of 74
95.3%
Misses roughly one word in 21, averaged over nine English test sets.
1
Stated by the leaderboard; we do not hold the list itself.
Percentage of words wrong on each set, lower better. Bars are scaled to this model's own worst case, not to the board.
The figures above come from the Open ASR Leaderboard, an independent public test that runs every model on the same recordings. It is the only measurement of transcription quality we know of, so there are no other scores to show.
These tests check whether a model follows instructions — a precondition for all the work above, but not a measure of how well that work is done, which is why they get no rating.
Every published score for this model8 scoresEvery figure we hold, from 8 boards, with who ran it and a link to the source — including the boards no rating above is built on.
Or rent it from someone else
Cheapest of 1 live listings. Picked at the widest standard context we hold, within one quantisation slice, so the numbers beside it are a price one host actually charges.
- per minute of audio
- $0.004
- Context served
- —
- Throughput
- Not measured
| Provider | Price per minute of audio | Context | Throughput | Trains on prompts | Logs prompts | Zero retention |
|---|---|---|---|---|---|---|
| ElevenLabs | $0.004 | not reported | not measured | Unknown | Unknown | Unknown |
Across the 1 listings we hold: 0 say they do not train on prompts, 0 say they do and 1 do not say. 0 appear in the zero-retention registry we check; the rest are unknown to us rather than confirmed either way.
When we formed this view
Dates behind this page
Prices last checked 6h ago
What we do not know about this model yet
- 1 of 1 listings publish no parameter list, so what their API accepts is unknown to us.
- Nothing we hold says whether an endpoint streams, so we do not show it either way.
- 1 of 1 listings do not say whether they train on prompts.
- We don't hold a list price for this model yet — the gap is ours, not the lab's.
- We hold no cached-input rate for any of its listings.
Licence and identifiers
What the licence allowsWe hold no licence record for this model. Inside are the identifiers you need to pull it — its Hugging Face repo where we have one, our slug and a machine-readable card.
Licence
Commercial API terms. We hold no licence record for this model, so there is nothing to summarise here.
Identifiers
- Modality record
- audio->text
- Catalogue slug
- zoom-scribe-v1