Context Aware Automatic Speech Recognition
GPT-Live-Transcribe 44.6%
In use Speech transcription systems are scored for semantic accuracy with and without free-form context.
OpenAI reports this internal benchmark for GPT-Live-Transcribe.
- Made by
- OpenAI
- Released
- July 2026
- Kind
- Speech recognition and translation
- Level
- Everyday
- Scored
- Graded by a model
- Answers
- Short answer
- Tasks
- Kept private
- Last in a launch post
- July 2026
- Last model added
- July 2026
1
Model scored in lab cards
1
Launch post lists it, from 1 lab
GPT-Live-Transcribe leads with 44.6%
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.
Source: Labs’ model cards
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | GPT-Live-Transcribe | 44.6% | Jul 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
Source: Labs’ model cards
One lab put it in a launch post in the last six months
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.
| Date | Launch post | Score | As the post writes it |
|---|---|---|---|
| Jul 29, 2026 | GPT-Live-Transcribe | 44.6 | Context Aware Automatic Speech Recognition semantic accuracy with free-form context |
More 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%