Voice AI BenchmarksBy

PROVIDERLAST 30 DAYS

official resource

Baseten voice AI models and benchmarks

Baseten is an inference platform for deploying open-source and custom AI models on dedicated GPUs.

Measured models
3
STTTTS
Best STT model#15 / 24
262ms
Whisper Large v3

Overview

Baseten serves models created by others rather than training its own. Each measured endpoint is a streaming WebSocket deployment from its model library, with hardware and concurrency chosen per deployment.

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
serves Whisper Large v3, Qwen3 ASR 1.7b
Text-to-Speech
serves Qwen3 TTS 1.7b

Speech-to-Text

Full STT dashboard

Ranked on Time to Final Segment against 24 measured models.

Time to Final Segmentms · lower is better · Baseten models markedEvery measured STT model on Time to Final Segment, with Baseten's models highlighted.
  1. #1STT RT v559 ms
  2. #2STT 166 ms
  3. #3Parakeet TDT 0.6B v378 ms
  4. #4Flux Multilingual93 ms
  5. #5Nova 394 ms
  6. #6Flux96 ms
  7. #7Nova 297 ms
leaders plus Baseten models · 17 other models in the full table
Word Error Rate% · lower is better · Baseten models markedEvery measured STT model on Word Error Rate, with Baseten's models highlighted.
  1. #1Universal 3.5 Pro3.1%
  2. #2resonant-13.4%
  3. #3Qwen3 ASR 1.7b3.7%
  4. #4Chirp 34.1%
  5. #5Whisper Large v3via Baseten4.2%
  6. #6Enhanced4.3%
  7. #7GPT-4o Transcribe4.6%
leaders plus Baseten models · 21 other models in the full table
Time to First Tokenms · lower is better · Baseten models markedEvery measured STT model on Time to First Token, with Baseten's models highlighted.
  1. #1Universal 3.5 Pro1038 ms
  2. #2Flux1081 ms
  3. #3Flux Multilingual1169 ms
  4. #4Parakeet TDT 0.6B v31214 ms
  5. #5Whisper Large v31305 ms
  6. #6STT 11423 ms
  7. #7Nova 31424 ms
leaders plus Baseten models · 15 other models in the full table
Benchmarked models with their Time to Final Segment over the last 30 days.
ModelHostTTFSRank
Whisper Large v3Together AI262 ms15th of 24
Qwen3 ASR 1.7bBaseten——

Text-to-Speech

Full TTS dashboard

Ranked on Time to First Audio against 26 measured models.

Time to First Audioms · lower is better · Baseten models markedEvery measured TTS model on Time to First Audio, with Baseten's models highlighted.
  1. #1vui87 ms
  2. #2TTS Flash 2112 ms
  3. #3Palabra TTS v1115 ms
  4. #4TTS 2177 ms
  5. #5Default235 ms
  6. #6TTS Rt v2257 ms
  7. #7TTS RT v1257 ms
leaders plus Baseten models · 19 other models in the full table
Word Error Rate% · lower is better · Baseten models markedEvery measured TTS model on Word Error Rate, with Baseten's models highlighted.
  1. #1TTS RT v13.8%
  2. #2TTS Rt v24.0%
  3. #3Eleven v3 Conversational4.3%
  4. #4Lightning v3.1 Pro4.4%
  5. #5Simba 3.24.4%
  6. #6TTS 24.6%
  7. #7S2.1 Pro4.7%
  8. #20Qwen3 TTS 1.7b5.6%
leaders plus Baseten models · 19 other models in the full table
Benchmarked models with their Time to First Audio over the last 30 days.
ModelHostTTFARank
Qwen3 TTS 1.7bBaseten——

Limits of this comparison

Coval measures three open-weight models served from Baseten dedicated endpoints: Whisper Large v3 and Qwen3-ASR 1.7B for transcription, and Qwen3-TTS 1.7B for synthesis.

  • Dedicated endpoints run on hardware reserved for a single customer, so their latency is not ranked against shared APIs here; accuracy is compared across the full field. Results describe Coval's deployments, not every configuration Baseten's library offers.

Official resources

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

Evaluate your own voice agent

Use Coval to test your production configuration, prompts and calls—not only the public benchmark endpoints.

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