PROVIDERLAST 30 DAYS

official resource

LMNT voice AI models and benchmarks

LMNT develops low-latency speech synthesis APIs and custom voices.

Measured models
1
TTS

Overview

LMNT's TTS endpoint offers multilingual synthesis and voice cloning.

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

Text-to-Speech
Blizzard

Ranked on Time to First Audio against 30 measured models.

Time to First Audioms · lower is better · LMNT models markedEvery measured TTS model on Time to First Audio, with LMNT's models highlighted.
  1. #2vui124 ms
  2. #3TTS Flash 2128 ms
  3. #4TTS 2176 ms
  4. #5Blizzard235 ms
  5. #6Neural236 ms
  6. #7Mist v3256 ms
leaders plus LMNT models · 23 other models in the full table
Word Error Rate% · lower is better · LMNT models markedEvery measured TTS model on Word Error Rate, with LMNT's models highlighted.
  1. #1TTS RT v13.7%
  2. #2TTS Rt v23.9%
  3. #3Neural4.3%
  4. #6Default4.6%
  5. #7S2.1 Pro4.6%
  6. #28Blizzard7.4%
leaders plus LMNT models · 22 other models in the full table
Benchmarked models with their Time to First Audio over the last 30 days.
ModelHostTTFARank
BlizzardLmnt235 ms5th of 30

Limits of this comparison

Coval measures the Blizzard model through LMNT's own infrastructure.

  • The benchmark does not rate custom-voice similarity or every LMNT voice and language.

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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