Benchmark Almanac

TimeSpeak

Models initiate speech at specified times while producing the requested content.

The launch post reports macro-averaged accuracy on an internal benchmark.

Released
May 2026
Kind
Speech recognition and translation
Level
Everyday
Scored
Graded by a model
Answers
Open-ended
Tasks
Kept private
Last in a launch post
May 2026, dropped before it saturated
Last model added
May 2026
1
Model scored in lab cards
1
Launch post lists it, from 1 lab

TML-Interaction-Small leads with 64.7%

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 TML-Interaction-Small 64.7%

Source: Labs’ model cards

#ModelScoreSettingDateSource
1 TML-Interaction-Small 64.7% May 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 Near the ceiling (85%) TML-Interaction-Small 0% 20% 40% 60% 80% 100% 2026 Near the ceiling (85%) TML-Interaction-Small

Source: Labs’ model cards

Labs headline it less often now, last in May 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.

Thinking Machines
DateLaunch postScoreAs the post writes it
May 11, 2026 TML-Interaction-Small 64.7 TimeSpeak macro-accuracy, internal

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%