Benchmark Almanac

Seed-TTS-eval

Models clone a voice from a short prompt and speak new text in English and Mandarin. Scored by word error rate from an ASR model and by speaker similarity.

Uses 1,000 Common Voice samples for English and 2,000 DiDiSpeech-2 samples for Mandarin, plus a hard Mandarin set. Repo has about 1,600 GitHub stars.

Released
June 2024
Kind
Speech recognition and translation
Level
Everyday
Scored
Checked automatically
Answers
Open-ended
Tasks
All public
Last in a launch post
March 2026, dropped before it saturated
Last model added
April 2026
1
Model scored in lab cards
4
Launch posts list it, from 1 lab
5
System cards report it, from 3 labs

Qwen3-TTS-12Hz-1.7B-Base leads with 0.77%

Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.

  1. 1 Qwen3-TTS-12Hz-1.7B-Base 0.77%

Source: Labs’ model cards

#ModelScoreSettingDateSource
1 Qwen3-TTS-12Hz-1.7B-Base 0.77% Jan 2026 Lab model card

Scores over time

All the scores we have, one dot each, so a model tested at several settings appears more than once.

Reported by the lab in its model card
0% 20% 40% 60% 80% 100% 2026 Qwen3-TTS-12Hz-1.7B-Base 0% 20% 40% 60% 80% 100% 2026 Qwen3-TTS-12Hz-1.7B-Base

Source: Labs’ model cards

Labs headline it less often now, last in March 2026

Launch posts from every lab that has listed it, one tick per post. Tall colored ticks include it, and short gray ones leave it out.

Qwen
DateLaunch postScoreAs the post writes it
Mar 30, 2026 Qwen3.5-Omni-Plus 1.35 Seed-en custom voice stability (Seed-zh 1.07, Seed-hard 6.24)
Jan 22, 2026 Qwen3-TTS-12Hz-1.7B-Base 0.77 SEEDtest-zh WER, Qwen3-TTS-12Hz-1.7B-Base
Sep 22, 2025 Qwen3-Omni-30B-A3B 1.39 SEED test-zh / test-en 1.07 / 1.39 (test-en recorded)
Mar 27, 2025 Qwen2.5-Omni-7B 2.32 SEED test-en content consistency, Qwen2.5-Omni-7B_RL (test-zh 1.42, test-hard 6.54)

5 system cards report it, from 3 labs

Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.

DateDocumentScoreAs the document writes itSection
Apr 17, 2026 Qwen3.5-Omni-Plus technical report SEED zero-shot TTS WER test-zh 0.99, test-en 1.26, no overall (Table 8) Capabilities
Feb 4, 2026 ERNIE 5.0 technical report SEED-TTS test-zh 1.35, test-en 1.54, WER, lower is better, no overall score (Table 8) Capabilities
Sep 22, 2025 Qwen3-Omni-30B-A3B technical report SEED test-zh 1.07, test-en 1.39, content consistency WER, lower is better, no overall score (Table 13) Capabilities
Sep 18, 2025 MiMo-Audio-7B-Instruct technical report Seed-TTS-Eval WER ZH 1.96, EN 5.37, ZH-Hard 14.14, lower is better, no overall score (Table 9) Capabilities
Mar 26, 2025 Qwen2.5-Omni-7B technical report SEED content consistency WER, Qwen2.5-Omni-7B RL test-zh 1.42, test-en 2.33, test-hard 6.54 (ICL 1.70, 2.72, 7.97). Speaker similarity RL 0.754, 0.641, 0.752. Lower WER is better, no overall score (Table 9) Capabilities

More in Audio and video

All 232 in Audio and video
  • Video-MMMU In use 300 expert-level lecture videos with questions testing perception, comprehension and adaptation of knowledge. Accuracy. Qwen 3.8 Max 88.7%
  • LVBench In use Hours-long video understanding with multiple-choice questions on reasoning, grounding and summarization. Gemini 4 Argon 91.7%
  • MMVU In use 3,000 expert-annotated questions on videos across 27 disciplines. Multiple-choice and open-ended accuracy. Qwen 3.8 Max 82.4%
  • MLVU In use Multi-task long video understanding (minutes to hours) with multiple-choice and generation tasks. Accuracy. Qwen 3.8 Max 90.8%
  • FLEURS In use Models transcribe read speech in 102 languages built from FLoRes-101 sentences. Model cards usually report word error rate, so lower scores are better. Phi-4-multimodal 4.00%
  • VoiceBench In use Spoken instructions with speaker, environment and content variation. Voice assistant responses scored by GPT judge or rules. Qwen3.5-Omni-Plus 93.1%