Mongolian Speech-to-Text Leaderboard
ElevenLabs Scribe v2Operating point: scribe_v2

ElevenLabs Scribe v2 — Mongolian Speech-to-Text Benchmark

Real results from the ElevenLabs Scribe v2 Batch API (enhanced operating point, language mn) evaluated across 4 Mongolian datasets and 265 audio samples. Every number below is measured — not marketing. WER, speed, and pricing are shown as-is, brutally honest.

Language:MNDiarization:noneSamples:265Run:Aug 19, 2026, 6:13 PMEndpoint:https://api.elevenlabs.io/v1/speech-to-text
06710072.9%
Accuracy

265/265 samples transcribed · 100% success rate

06710027.1%
Word Error Rate

Lower is better · across 265 samples

Headline metrics
Character Error Rate10.6%
Avg speed factor1.51×realtime multiple
Total speed factor1.51×
Avg latency / sample4.7s
Total audio processed1849.3s30.8 min

Pricing

ElevenLabs Scribe v2 list pricing for batch transcription. No discounts, no negotiated rates applied — the raw per-minute rate.

Per 1k minutes
$3.7
batch
Per minute
$0.0037
effective
Per 1k min (these 30.8 min)
$6.84
would cost
Open source?
proprietary

Pricing source: ElevenLabs Scribe v2 public pricing. Duudlaga Flow is shown for context only — this page isolates ElevenLabs Scribe v2 so the number is not padded by our own product.

WER & CER by dataset

Word and character error rates per dataset. Lower is better — and these are the real ElevenLabs Scribe v2 numbers, which are weak on Common Voice 24.

Common Voice 24 (MN)
Source dataset →
WER
28.5%
CER
10.6%
Shunya Labs Mongolian Speech
Source dataset →
WER
19.2%
CER
6.3%
Common Voice 20 (MN)
Source dataset →
WER
29.4%
CER
11.4%
Modern Voice
WER
29.8%
CER
13%
WERCER

Dataset summary

Aggregate accuracy, speed, and timing for each dataset.

DatasetSourceSamplesSuccessWERCERAccuracySpeedAudio (s)Proc (s)
Common Voice 24 (MN)Hugging Face →5959/5928.5%10.6%71.5%1.33×330.6s248.1s
Shunya Labs Mongolian SpeechHugging Face →6060/6019.2%6.3%80.8%1.74×645.1s370.3s
Common Voice 20 (MN)Hugging Face →5454/5429.4%11.4%70.6%1.41×269.8s190.7s
Modern Voice9292/9229.8%13%70.2%1.45×603.8s416s

WER vs speed — per sample

Each dot is one audio sample. The sweet spot is the bottom-left (low error, fast). ElevenLabs Scribe v2 sits high on error for many Common Voice 24 samples.

Per-sample results

Ground truth shown verbatim in the Expected column. The result column highlights only the words ElevenLabs Scribe v2 got wrong, in red — no strikethrough/swap gymnastics, just the mistakes.

265 rows
redwrong word in the resultplaincorrectly transcribedExpected column shown verbatim as ground truth
#AudioSampleDatasetExpected (ground truth)ElevenLabs Scribe v2 resultWERCERI/D/S
1btsee_0001Common Voice 24 (MN)Гэхдээ амьсгал хураахаасаа өмнө танд мэдэж байгаагаа хэлье.Гэхдээ амьсгал хураахаасаа өмнө танд мэдэж байгаагаа хэлье0.0%0.0%0/0/0
2btsee_0002Common Voice 24 (MN)Надад заяасан аз жаргал гэдэг ердөө гуравхан сарын хугацаатай байсан гэж үү?Надад заяасан аж жаргал гэдэг ердөө гуравхан сарын хугацаатай байсан гэж үү?8.3%1.3%0/0/1
3btsee_0003Common Voice 24 (MN)Одоо бид өөрсдөө өвчин эмгэгээсээ салахыг хичээцгээе.Одоо бид өөрсдөө өвчин эмнэлгээсээ салахыг хичээцгээе.14.3%3.8%0/0/1
4btsee_0004Common Voice 24 (MN)Би бол голдуу хээрээр гэр, хэцээр дэр хийж явдаг хүн.Би бол голдуй хээрээр гэр, хэцээр дэр хийж явдаг хүн.10.0%2.0%0/0/1
5btsee_0005Common Voice 24 (MN)Хан хурмаст уурлаж, Болдоггүй Бор өвгөнийг хор луугаараа ниргүүлэхээр явуулжээ.Хан хурмаст уулс болдоггүй бороо өгнө. Хоёр луугаар нэргүүлэхээр явагч70.0%26.0%0/0/7
6btsee_0006Common Voice 24 (MN)Алив наашаа ороод ир гээд гэртээ оров.Алив наашаа ороод ир гээд гэртээ оров.0.0%0.0%0/0/0
7btsee_0007Common Voice 24 (MN)Өө өндөр дээдэс таны тухайд би баталж чадахгүй.Өө, өндөр дээдс таны тухайд би ботолг чадахгүй25.0%8.7%0/0/2
8btsee_0008Common Voice 24 (MN)Харин гурав дахь удаагаас эхлэн хүмүүсийг сонирхож эхлэв.Харин гурав дахь удаагаас эхлэн хүмүүсийг сонирхож эхлэв.0.0%0.0%0/0/0
9btsee_0009Common Voice 24 (MN)Та нар очингуутаа шөл л өгч үз.Та нар очгондоо шүлэл өгч үз42.9%30.0%0/1/2
10btsee_0010Common Voice 24 (MN)Ерөөсөө литр үйлдвэрээсээ салаагүй явсан юм чинь.Эрүүлсээл үйлдвэрээсээ салаагүй явсан юм чинь28.6%20.8%0/1/1
Page 1 of 27

Methodology

How these numbers were produced.

Provider: ElevenLabs Scribe v2 (ElevenLabs Scribe v2 hosted transcription (language_code=mn).).

Endpoint https://api.elevenlabs.io/v1/speech-to-text. Language mn. Operating point scribe_v2. Diarization none.

Datasets: Common Voice 24 (MN), Shunya Labs Mongolian Speech, Common Voice 20 (MN), Modern Voice — 265 samples, 1849.3s of audio total.

Dataset source URLs:

Metrics: WER and CER are computed with a standard word/character Levenshtein alignment, normalized for case and punctuation. Accuracy = 100 − WER. Speed factor = audio duration ÷ processing time (× realtime). All requests are real ElevenLabs Scribe v2 Batch API calls, not cached or simulated.

Diff highlighting: The result column aligns to the ground truth and colors every substitution and insertion red. Deletions (words missing from the result) are not shown in the result column — the Expected column already holds the full ground truth as-is.

Generated by the ElevenLabs Scribe v2 Benchmark Runner · ElevenLabs Scribe v2 Batch API v2 · run Aug 19, 2026, 6:13 PM