Mistral AIAudio modelPublic preview

Voxtral Small Transcribe 3

PopularityRank 670 of 875

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Summary

Voxtral Small Transcribe 3 is Mistral's transcription model with context biasing and speaker recognition. Its model card gives a rounded 32k context but no exact token count. The model supports timestamps and vocabulary to guide recognition of domain terms.

All benchmark results

Every published result with its source, test setup and comparison models.

Show all 42 published benchmark results

Measurements without matching peer values

These measurements have no matching peer values under the same test conditions. Their original values and sources remain available here.

Diarization benchmark cpWER (Show measurement, test conditions, and source)

Source value: 18.4
Score: 18.4
Metric: cpWER
Unit: %
Category: speaker diarization
Direction: Lower is better
Source type: vendor-reported
Evaluator: Mistral Voxtral 3 announcement and benchmark tables
Status: active
Retrieved at: 2026-10-24
Methodology: Vendor-reported result. Macro-average over AMI-IHM, AMI-SDM, Switchboard, Switchboard CallHome, and AISHELL-4. Thirty-minute AMI and AISHELL variants are used.

Source Mistral Voxtral 3 announcement and benchmark tables

Artificial Analysis weighted WER index (Show measurement, test conditions, and source)

Source value: 2.1
Score: 2.1
Metric: weighted WER
Unit: %
Category: speech recognition
Direction: Lower is better
Source type: vendor-reported
Evaluator: Mistral Voxtral 3 announcement and benchmark tables
Status: active
Retrieved at: 2026-10-24
Methodology: Vendor-reported result. Weighted WER index across VoxPopuli, Earnings22, and AgentTalk.

Source Mistral Voxtral 3 announcement and benchmark tables

Earnings22 keyphrase recall: without context (Show measurement, test conditions, and source)

Source value: 81.4
Score: 81.4
Metric: keyphrase recall
Unit: %
Category: keyphrase recognition
Direction: Higher is better
Source type: vendor-reported
Evaluator: Mistral Voxtral 3 announcement and benchmark tables
Status: active
Retrieved at: 2026-10-24
Methodology: Vendor-reported result. Small Transcribe 3 on Earnings22. Context mode: without context. Evaluation includes context vocabulary, speaker names, and random distractors from 0 to 100.

Source Mistral Voxtral 3 announcement and benchmark tables

Earnings22 keyphrase recall: with context (Show measurement, test conditions, and source)

Source value: 94.6
Score: 94.6
Metric: keyphrase recall
Unit: %
Category: keyphrase recognition
Direction: Higher is better
Source type: vendor-reported
Evaluator: Mistral Voxtral 3 announcement and benchmark tables
Status: active
Retrieved at: 2026-10-24
Methodology: Vendor-reported result. Small Transcribe 3 on Earnings22. Context mode: with context. Evaluation includes context vocabulary, speaker names, and random distractors from 0 to 100.

Source Mistral Voxtral 3 announcement and benchmark tables

Omi Medical batch: Medical-term WER (Show measurement, test conditions, and source)

Source value: 1.04
Score: 1.04
Metric: Medical-term WER
Unit: %
Benchmark version: Omi report edition 2026-10-18.1
Category: medical-transcription
Direction: Lower is better
Sample: 2872
Source type: vendor-reported
Evaluator: Omi Medical benchmark v1.1
Status: disputed
Retrieved at: 2026-10-24
Methodology: Vendor-reported result. Rank 2 in Omi's batch table. Batch transcription on the 1,513-recording English medical corpus. Rank 2; Omi internal row profile voxtral-small-transcribe-3. Metric denominator: 2872.
Context: Omi labels its report edition 2026-10-18.1 and Voxtral accuracy rows only by month (2026-10); batch timing is dated October 18 and realtime timing October 19, before Mistral announced public preview on October 20. The exact endpoint/build is not identified. These are disputed observations, not definitive measurements of the post-release model.

Source Omi Medical benchmark v1.1

Omi Medical batch: Overall WER (Show measurement, test conditions, and source)

Source value: 5.58
Score: 5.58
Metric: Overall WER
Unit: %
Benchmark version: Omi report edition 2026-10-18.1
Category: medical-transcription
Direction: Lower is better
Sample: 63815
Source type: vendor-reported
Evaluator: Omi Medical benchmark v1.1
Status: disputed
Retrieved at: 2026-10-24
Methodology: Vendor-reported result. Rank 2 in Omi's batch table. Batch transcription on the 1,513-recording English medical corpus. Rank 2; Omi internal row profile voxtral-small-transcribe-3. Metric denominator: 63815.
Context: Omi labels its report edition 2026-10-18.1 and Voxtral accuracy rows only by month (2026-10); batch timing is dated October 18 and realtime timing October 19, before Mistral announced public preview on October 20. The exact endpoint/build is not identified. These are disputed observations, not definitive measurements of the post-release model.

Source Omi Medical benchmark v1.1

Omi Medical batch: Drug-name errors (Show measurement, test conditions, and source)

Source value: 0.68
Score: 0.68
Metric: Drug-name errors
Unit: %
Benchmark version: Omi report edition 2026-10-18.1
Category: medical-transcription
Direction: Lower is better
Sample: 442
Source type: vendor-reported
Evaluator: Omi Medical benchmark v1.1
Status: disputed
Retrieved at: 2026-10-24
Methodology: Vendor-reported result. Rank 2 in Omi's batch table. Batch transcription on the 1,513-recording English medical corpus. Rank 2; Omi internal row profile voxtral-small-transcribe-3. Metric denominator: 442.
Context: Omi labels its report edition 2026-10-18.1 and Voxtral accuracy rows only by month (2026-10); batch timing is dated October 18 and realtime timing October 19, before Mistral announced public preview on October 20. The exact endpoint/build is not identified. These are disputed observations, not definitive measurements of the post-release model.

Source Omi Medical benchmark v1.1

Omi Medical batch: Dose/unit matches (Show measurement, test conditions, and source)

Source value: 84.04
Score: 84.04
Metric: Dose/unit matches
Unit: %
Benchmark version: Omi report edition 2026-10-18.1
Category: medical-transcription
Direction: Higher is better
Sample: 94
Source type: vendor-reported
Evaluator: Omi Medical benchmark v1.1
Status: disputed
Retrieved at: 2026-10-24
Methodology: Vendor-reported result. Rank 2 in Omi's batch table. Batch transcription on the 1,513-recording English medical corpus. Rank 2; Omi internal row profile voxtral-small-transcribe-3. Metric denominator: 94.
Context: Omi labels its report edition 2026-10-18.1 and Voxtral accuracy rows only by month (2026-10); batch timing is dated October 18 and realtime timing October 19, before Mistral announced public preview on October 20. The exact endpoint/build is not identified. These are disputed observations, not definitive measurements of the post-release model.

Source Omi Medical benchmark v1.1

Omi Medical batch: Dose/unit errors (Show measurement, test conditions, and source)

Source value: 15.96
Score: 15.96
Metric: Dose/unit errors
Unit: %
Benchmark version: Omi report edition 2026-10-18.1
Category: medical-transcription
Direction: Lower is better
Sample: 94
Source type: vendor-reported
Evaluator: Omi Medical benchmark v1.1
Status: disputed
Retrieved at: 2026-10-24
Methodology: Vendor-reported result. Rank 2 in Omi's batch table. Batch transcription on the 1,513-recording English medical corpus. Rank 2; Omi internal row profile voxtral-small-transcribe-3. Metric denominator: 94.
Context: Omi labels its report edition 2026-10-18.1 and Voxtral accuracy rows only by month (2026-10); batch timing is dated October 18 and realtime timing October 19, before Mistral announced public preview on October 20. The exact endpoint/build is not identified. These are disputed observations, not definitive measurements of the post-release model.

Source Omi Medical benchmark v1.1

Omi Medical batch: Dose precision (Show measurement, test conditions, and source)

Source value: 91.86
Score: 91.86
Metric: Dose precision
Unit: %
Benchmark version: Omi report edition 2026-10-18.1
Category: medical-transcription
Direction: Higher is better
Sample: 86
Source type: vendor-reported
Evaluator: Omi Medical benchmark v1.1
Status: disputed
Retrieved at: 2026-10-24
Methodology: Vendor-reported result. Rank 2 in Omi's batch table. Batch transcription on the 1,513-recording English medical corpus. Rank 2; Omi internal row profile voxtral-small-transcribe-3. Metric denominator: 86. Precision denominator is the number of predicted dose/unit events.
Context: Omi labels its report edition 2026-10-18.1 and Voxtral accuracy rows only by month (2026-10); batch timing is dated October 18 and realtime timing October 19, before Mistral announced public preview on October 20. The exact endpoint/build is not identified. These are disputed observations, not definitive measurements of the post-release model.

Source Omi Medical benchmark v1.1

Omi Medical batch: Dose F1 (Show measurement, test conditions, and source)

Source value: 87.78
Score: 87.78
Metric: Dose F1
Unit: %
Benchmark version: Omi report edition 2026-10-18.1
Category: medical-transcription
Direction: Higher is better
Source type: vendor-reported
Evaluator: Omi Medical benchmark v1.1
Status: disputed
Retrieved at: 2026-10-24
Methodology: Vendor-reported result. Rank 2 in Omi's batch table. Batch transcription on the 1,513-recording English medical corpus. Rank 2; Omi internal row profile voxtral-small-transcribe-3. F1 combines reference and predicted events.
Context: Omi labels its report edition 2026-10-18.1 and Voxtral accuracy rows only by month (2026-10); batch timing is dated October 18 and realtime timing October 19, before Mistral announced public preview on October 20. The exact endpoint/build is not identified. These are disputed observations, not definitive measurements of the post-release model.

Source Omi Medical benchmark v1.1

FLEURS 45 forced transcription WER (Show measurement, test conditions, and source)

Source value: 4
Score: 4
Metric: WER
Unit: %
Category: speech recognition
Direction: Lower is better
Source type: vendor-reported
Evaluator: Mistral Voxtral 3 announcement and benchmark tables
Status: active
Retrieved at: 2026-10-24
Methodology: Vendor-reported result. Macro-average across 45 FLEURS languages, forced transcription mode. WER is used except CER for Japanese, Korean, Thai, and Chinese.

Source Mistral Voxtral 3 announcement and benchmark tables

Page 1 of 4

Popularity compared

How often the model is searched for, used and mentioned, compared with every model of its category.

Popularity index

0 to 100, higher is more popular

20 of 83 models

pyannote Community-173

Nemotron-3-Diarization57

Gemini 3.5 Transcribe52

Confucius4-R2T252

Granite Speech 5.0 470M TurboCTC52

Kokoro-82M51

Nova-351

Fish Audio S2 Pro51

NVIDIA Nemotron 3.5 Transcribe50

Granite Speech 5.0 470M TurboCTC NC50

Orukeet49

Lyria 3.547

Gemini 3.5 Live Translate46

Phonon-244

Aura-244

Gemini 3.1 Flash TTS44

MiniMax-Music341

Audio8-ASR-Infinite41

GPT-Realtime 2.141

Voxtral Small Transcribe 30

pyannote Community-1

Nemotron-3-Diarization

Gemini 3.5 Transcribe

Confucius4-R2T2

Granite Speech 5.0 470M TurboCTC

Kokoro-82M

Nova-3

Fish Audio S2 Pro

NVIDIA Nemotron 3.5 Transcribe

Granite Speech 5.0 470M TurboCTC NC

Orukeet

Lyria 3.5

Gemini 3.5 Live Translate

Voxtral Small Transcribe 3

As of November 2026 · Source: gradually.ai popularity index

Over time

Weekly values from November 1, 2026 to November 5, 2026

Voxtral Small Transcribe 3Amazon Nova 2 SonicEleven Multilingual STS v2Eleven Music v2.5Eleven Text to Sound v2

All specifications

Architecture

Parameters: not published; Source: Parameters

Input and output

Context length: 32k, stated as a rounded value; no exact token count published; Source: Context length
Input: Audio with optional context vocabulary; Source: Input
Output: Transcript with timestamps and speaker segmentation; Source: Output
Context values by source: 32k, stated as a rounded value; Source: Context values by source

Watermarking and provenance

AI watermarking refers to invisible signals embedded in the output. Visible marks and provenance metadata are listed separately. Unknown means there is insufficient evidence for that particular field.

AI watermarking: Unknown; no source
Watermarking technique: Not known; no source

Licence and access

Release: Public preview since October 20, 2026; Source: Release
Access: Mistral API, public preview; Source: Access
Release: Oct 20, 2026; Source: Release
Source status: public preview; Source: Source status

API

API model ID: voxtral-small-transcribe-3-0; Source: API model ID

Further details

Language support in the current documentation: The language table lists voxtral-small-transcribe-3-0 with support for 50 languages.; Source: Language support in the current documentation
Model ID in the API examples: Official request docs show the model string voxtral-small-transcribe-3. (The model card uses voxtral-small-transcribe-3-0; the request documentation omits trailing '-0' and does not explain whether they are aliases.); Source: Model ID in the API examples

Prices

Price: USD 0.004 per audio minute; cached rate USD 0.0004 per minuteSource
Price per audio minute in USD: 0.004Source
Cached price per audio minute in USD: 0.0004Source
Artificial Analysis listed price per 1,000 minutes: 4Source

Sources and data date

Show all 35 sources

Benchmark sources at a glance

Which independent evaluators tested this model. This is coverage, not a quality ranking.

Evaluator	Test series	Composite indices	Recorded active measurements
Artificial Analysis	0	0	14

Without vendor claims and historical or disputed results; those stay labelled in the single values. 14 measurements are not yet assigned to a test series.

Type	Evidence and data date
Research status	Research date October 24, 2026. 100 source URLs checked. This documents the inspected sources, not an exhaustive inventory of every publication.
Not published	Model weights and license Note The public API model card does not state downloadable weights or an open-source license.
Not found in the inspected sources	FLEURS results by language Note The announcement publishes macro-averages for FLEURS rather than per-language scores.
Not found in the inspected sources	Exact context length in tokens Note The model card states a rounded 32k context but gives no exact token count; do not infer 32,000 or 32,768.
Unresolved	Exact Omi endpoint and model build Note Omi names the product and an internal profile key but not the exact API endpoint or model metadata. The timing conflict prevents a definitive match to the public version announced on October 20.
Unresolved	Model card to request ID crosswalk Note The model card uses voxtral-small-transcribe-3-0, while the request example uses voxtral-small-transcribe-3. Public documentation does not say whether the identifiers are interchangeable.
Not published	Artificial Analysis per-dataset utterance counts and WER confidence intervals Note The page/methodology reports roughly eight benchmark hours but no exact utterance counts or uncertainty interval for the WER values.
Additional source	Mistral Voxtral 3 announcement (retrieved October 24, 2026) · Mistral Voxtral 3 announcement · Editorial description reviewed October 24, 2026
Additional source	Mistral audio models overview (retrieved October 24, 2026)
Additional source	Mistral speech transcription overview (retrieved October 24, 2026)
Additional source	Mistral model changelog (retrieved October 24, 2026)
Additional source	Mistral inference pricing (retrieved October 24, 2026)
Additional source	Voxtral Small Transcribe 3 model card (retrieved October 24, 2026) · Voxtral Small Transcribe 3 model card · Editorial description reviewed October 24, 2026
Additional source	Omi Medical benchmark v1.1 (retrieved October 24, 2026)
Additional source	Artificial Analysis (retrieved October 24, 2026)
Additional source	Open Danish ASR Leaderboard (retrieved October 24, 2026)
Additional source	Model metadata (retrieved October 24, 2026)1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Additional source	OpenRouter: Popularity index (derived), CC BY 4.0
Additional source	Vercel AI Gateway: Popularity index (derived), CC BY 4.0
Additional source	Ollama: cumulative downloads for the popularity index
Additional source	Replicate: cumulative runs for the popularity index
Additional source	Google Trending Now: limited feed selection for Germany and the US
Additional source	Creative Commons Attribution 4.0