Voice AI BenchmarksBy

PROVIDERLAST 30 DAYS

official resource

Gladia voice AI models and benchmarks

Gladia lists 1 STT model in Coval. Its fastest dated STT result is Solaria 1 at mean 803 ms time to final segment (27th of 28) among STT systems, with 7.1% WER. Results cover the last 30 days. Last measured .

Gladia builds real-time and asynchronous speech recognition services.

Measured models
1
STT
Best STT model#27 / 28
803ms
Solaria 1

Overview

The measured service includes multilingual transcription, translation, code switching and vocabulary controls, while Coval ranks its STT outcomes only.

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
Solaria 1

Speech-to-Text

Full STT dashboard

Ranked on Time to Final Segment against 28 measured models.

Time to Final Segmentms · lower is better · Gladia models markedEvery measured STT model on Time to Final Segment, with Gladia's models highlighted.
  1. #1Qwen3 ASR 1.7b39 ms
  2. #2Qwen3 ASR Fast46 ms
  3. #3STT RT v557 ms
  4. #4STT 165 ms
  5. #5Parakeet TDT 0.6B v381 ms
  6. #6Nova 389 ms
  7. #7Nova 292 ms
  8. #27Solaria 1803 ms
leaders plus Gladia models · 20 other models in the full table
Word Error Rate% · lower is better · Gladia models markedEvery measured STT model on Word Error Rate, with Gladia's models highlighted.
  1. #1Universal 3.5 Pro3.1%
  2. #2Qwen3 ASR Fast3.2%
  3. #3resonant-13.4%
  4. #4Gemini 3.5 Transcribe Live3.9%
  5. #5Chirp 34.1%
  6. #6Qwen3 ASR 1.7b4.1%
  7. #7Enhanced4.3%
  8. #24Solaria 17.1%
leaders plus Gladia models · 22 other models in the full table
Time to First Tokenms · lower is better · Gladia models markedEvery measured STT model on Time to First Token, with Gladia's models highlighted.
  1. #1Whisper Large v3via Baseten912 ms
  2. #2Qwen3 ASR 1.7b931 ms
  3. #3Universal 3.5 Pro1040 ms
  4. #4Flux1076 ms
  5. #5Flux Multilingual1163 ms
  6. #6Parakeet TDT 0.6B v31215 ms
  7. #7Whisper Large v3via Together AI1338 ms
  8. #18Solaria 11801 ms
leaders plus Gladia models · 18 other models in the full table
TTFS vs WER — Gladia vs every measured modelEach point is one measured STT model · Gladia models highlighted · 30-day averagesTime to Final Segment against Word Error Rate for every measured STT model, with Gladia's models highlighted.
Qwen3 ASR 1.7b — 39 ms, 4.1%Qwen3 ASR Fast — 46 ms, 3.2%STT RT v5 — 57 ms, 5.7%STT 1 — 65 ms, 4.4%Parakeet TDT 0.6B v3 — 81 ms, 11.2%Nova 3 — 89 ms, 6.2%Nova 2 — 92 ms, 7.9%Flux Multilingual — 98 ms, 8.8%Flux — 99 ms, 6.6%Ink 2 — 122 ms, 4.8%Whisper Large v3 via Baseten — 125 ms, 5.6%Scribe v2 Realtime — 133 ms, 5.5%Universal 3.5 Pro — 173 ms, 3.1%Grok STT — 207 ms, 4.6%Default via Speechmatics — 209 ms, 5.4%Pulse — 212 ms, 5.3%Default via Gradium — 246 ms, 10.0%resonant-1 — 264 ms, 3.4%Whisper Large v3 via Together AI — 296 ms, 8.5%Enhanced — 299 ms, 4.3%Gemini 3.5 Transcribe Live — 305 ms, 3.9%Voxtral Mini Transcribe Realtime 2602 — 400 ms, 6.2%GPT Realtime Whisper — 551 ms, 5.1%GPT-4o mini Transcribe — 690 ms, 4.9%GPT-4o Transcribe — 754 ms, 4.6%Chirp 3 — 776 ms, 4.1%Chirp 2 — 873 ms, 4.9%Solaria 1 — 803 ms, 7.1%
Benchmarked models with their Time to Final Segment over the last 30 days.
ModelHostTTFSRank
Solaria 1Gladia803 ms27th of 28

How fast are Gladia's STT models?

Solaria 1 measures mean 803 ms time to final segment (27th of 28) among STT systems. Last measured 2026-09-15.

How accurate are Gladia's STT models?

Solaria 1 measures 7.1% word error rate (24th of 30) among STT systems. Last measured 2026-09-15.

Which Gladia model is fastest?

Its fastest dated STT result is Solaria 1 at mean 803 ms time to final segment (27th of 28) among STT systems, with 7.1% WER. Last measured 2026-09-15.

Limits of this comparison

Coval measures the Solaria 1 streaming endpoint served by Gladia.

  • Translation quality and the wider Gladia audio-intelligence platform are outside the current public metrics.

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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