MultiChallenge Audio (OpenAI)
gpt-realtime 30.5% Dropped
Speech-to-speech models answer an audio-friendly subset of MultiChallenge multi-turn questions that OpenAI converted from text to speech. Scored on instruction following accuracy.
OpenAI built it for the gpt-realtime launch on 2025-08-28. It differs from Scale's later Audio MultiChallenge (audio-mc), which uses native audio conversations.
Made by OpenAI Released Aug 2025 Audio understanding and voice Tasks kept private Last in a launch post Aug 2025 , dropped before it saturated
Last model added Aug 2025
- Level
- Everyday Most adults, without training
- Scored
- Graded by a model A language model scores each response, usually against a rubric.
- Answers
- Open-ended Free-form text, documents, designs or media judged as a whole.
1
Model scored in lab cards
1
Launch post lists it, from 1 lab
gpt-realtime leads with 30.5%
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 gpt-realtime 30.5%
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | gpt-realtime | 30.5% | Aug 2025 | 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
No launch post has listed it since Aug 2025
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 |
|---|---|---|---|
| 28 Aug 2025 | gpt-realtime | 30.5 | MultiChallenge (Audio), Instruction Following |
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%
- 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%
- TVBench In use Models answer multiple-choice questions on 10 temporal video tasks, such as action counting and ordering, that static frames cannot solve. Scored by accuracy. Qwen 3.8 Max 81.9%