PROVIDERLAST 30 DAYS

official resource

ElevenLabs voice AI models and benchmarks

ElevenLabs (Eleven Labs, 11Labs) lists 3 STT and TTS models in Coval. Fastest dated mean latency over 30 days: STT: Scribe v2 Realtime at 122 ms TTFS, with 4.4% WER. TTS: Flash v2.5 at 192 ms TTFA, with 1.8% WER. Last measured .

ElevenLabs develops speech generation and transcription APIs.

Measured models
3
STTTTS

Overview

The provider spans STT and TTS as a first-party host, with separate models for real-time transcription, low-latency speech and conversational expression.

Every model below is measured daily on the same fixed inputs and ranked against the full field, never blended into a company score.

Model lineup

Speech-to-Text
Scribe v2 Realtime

Ranked on Time to Final Segment against 29 measured models.

Time to Final Segmentms · lower is better · ElevenLabs models markedEvery measured STT model on Time to Final Segment, with ElevenLabs's models highlighted.
  1. #1Qwen3 ASR 1.7b39 ms
  2. #2STT RT v545 ms
  3. #4STT 167 ms
  4. #5Nova 386 ms
  5. #6Nova 287 ms
leaders plus ElevenLabs models · 21 other models in the full table
Word Error Rate% · lower is better · ElevenLabs models markedEvery measured STT model on Word Error Rate, with ElevenLabs's models highlighted.
  1. #4resonant-12.6%
  2. #5Qwen3 ASR 1.7b2.9%
  3. #7Chirp 33.2%
leaders plus ElevenLabs models · 23 other models in the full table
Time to First Tokenms · lower is better · ElevenLabs models markedEvery measured STT model on Time to First Token, with ElevenLabs's models highlighted.
  1. #1Whisper Large v3via Baseten924 ms
  2. #2Qwen3 ASR 1.7b946 ms
  3. #5Flux1091 ms
  4. #7STT 11205 ms
leaders plus ElevenLabs models · 19 other models in the full table
Benchmarked models with their Time to Final Segment over the last 30 days.
ModelHostTTFSRank
Scribe v2 RealtimeElevenLabs122 ms10th of 29

Ranked on Time to First Audio against 32 measured models.

Time to First Audioms · lower is better · ElevenLabs models markedEvery measured TTS model on Time to First Audio, with ElevenLabs's models highlighted.
  1. #1vui59 ms
  2. #2Default63 ms
  3. #4TTS Flash 291 ms
  4. #5Qwen3 TTS 1.7b107 ms
  5. #6Simba 3.0111 ms
  6. #7Palabra TTS120 ms
  7. #11Flash v2.5192 ms
leaders plus ElevenLabs models · 23 other models in the full table
Word Error Rate% · lower is better · ElevenLabs models markedEvery measured TTS model on Word Error Rate, with ElevenLabs's models highlighted.
leaders plus ElevenLabs models · 23 other models in the full table
Benchmarked models with their Time to First Audio over the last 30 days.
ModelHostTTFARank
Flash v2.5ElevenLabs192 ms11th of 32
Eleven v4 TurboElevenLabs201 ms12th of 32

How fast are ElevenLabs's STT and TTS models?

Scribe v2 Realtime measures mean 122 ms time to final segment (10th of 29) among STT systems. Last measured 2026-10-14. Flash v2.5 measures mean 192 ms time to first audio (11th of 32) among TTS systems. Last measured 2026-10-14. Eleven v4 Turbo measures mean 201 ms time to first audio (12th of 32) among TTS systems. Last measured 2026-10-14.

How accurate are ElevenLabs's STT and TTS models?

Scribe v2 Realtime measures 4.4% word error rate (15th of 31) among STT systems. Last measured 2026-10-14. Eleven v4 Turbo measures 1.7% word error rate (12th of 32) among TTS systems. Last measured 2026-10-14. Flash v2.5 measures 1.8% word error rate (20th of 32) among TTS systems. Last measured 2026-10-14.

Which ElevenLabs model is fastest?

Its fastest dated STT result is Scribe v2 Realtime at mean 122 ms time to final segment (10th of 29) among STT systems, with 4.4% WER. Last measured 2026-10-14. Its fastest dated TTS result is Flash v2.5 at mean 192 ms time to first audio (11th of 32) among TTS systems, with 1.8% WER. Last measured 2026-10-14.

Limits of this comparison

Coval measures Scribe on incoming audio and Eleven Flash plus Eleven v3 on fixed synthesis prompts.

  • The benchmarks do not score voice cloning similarity, subjective naturalness or every language and voice in the ElevenLabs catalogue.

Official resources

Same datasets, prompts and metric definitions for every model, measured by Coval’s open-source runner. Full methodology on the overview.

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